Journal of Intelligent & Fuzzy Systems - Volume 39, issue 3

Authors: Hamidi, Mohammad | Rahmati, Marzieh | Rezaei, Akbar

Article Type: Research Article

Abstract: According to Boolean logic, a disjunctive normal form (DNF) is a canonical normal form of a logical formula consisting of a disjunction of conjunctions (it can also be described as an OR of AND’s). For each table an arbitrary T.B.T is given (total binary truth table) Boolean expression can be written as a disjunctive normal form. This paper considers a notation of a T.B.T, introduces a new concept of the hypergraphable Boolean functions and the Boolean functionable hypergraphs with respect to any given T.B.T. This study defines a notation of unitors set on switching functions and proves that every T.B.T …corresponds to a minimum Boolean expression via unitors set and presents some conditions on a T.B.T to obtain a minimum irreducible Boolean expression from switching functions. Indeed, we generate a switching function in different way via the concept of hypergraphs in terms of Boolean expression in such a way that it has a minimum irreducible Boolean expression, for every given T.B.T. Finally, an algorithm is presented. Therefore, a Python programming(with complete and original codes) such that for any given T.B.T, introduces a minimum irreducible switching expression. Show more

Keywords: Switching function, hypergraphable Boolean function, Boolean functionable hypergraph, Boolean function–based hypergraph, Unitor, T.B.T.

DOI: 10.3233/JIFS-191230

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2845-2859, 2020

Authors: Sun, Qiong | Tan, Zhiyong | Zhou, Xiaolu

Article Type: Research Article

Abstract: In this study, support vector machine (SVM) and back-propagation (BP) neural networks were combined to predict the workload of cloud computing physical machine, so as to improve the work efficiency of physical machine and service quality of cloud computing. Then, the SVM and BP neural network was simulated and analyzed in MATLAB software and compared with SVM, BP and radial basis function (RBF) prediction models. The results showed that the average error of the SVM and BP based model was 0.670%, and the average error of SVM, BP and RBF was 0.781%, 0.759% and 0.708%, respectively; in the multi-step prediction, …the prediction accuracy of SVM, BP, RBF and SVM + BP in the first step was 89.3%, 94.6%, 96.3% and 98.5%, respectively, the second step was 87.4%, 93.1%, 95.2% and 97.8%, respectively, the third step was 83.5%, 90.3%, 93.1% and 95.7%, the fourth step was 79.1%, 87.4%, 90.5% and 93.2%, respectively, the fifth step was 75.3%, 81.3%, 85.9% and 91.1% respectively, and the sixth step was 71.1%, 76.6%, 82.1% and 89.4%, respectively. Show more

Keywords: Back propagation neural network, support vector machine, cloud computing, workload prediction

DOI: 10.3233/JIFS-191266

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2861-2867, 2020

Authors: Chang, Shih-Jui | Hsu, Chi-I | Lin, Chin-Tsai

Article Type: Research Article

Abstract: This research combines the Fuzzy Analytic Hierarchy Process (FAHP) with Case-Based Reasoning (CBR) to evaluate the intention of adoption of web ATM services. Compared with physical ATM service, web ATM allows users to perform financial transactions over the internet conveniently. Based on literature and considering the characteristics of web ATM, this study constructs a model for web ATM adoption that comprises three dimensions: The knowledge, the potential value, and the security. 222 valid user questionnaires are collected, and factor analysis is used to verify the factor structure of the decision hierarchy. FAHP is then used to calculate the weights of …criteria with six experts through pairwise comparisons. Finally, FAHP weights are integrated into a CBR prediction mechanism for evaluating a user’s adoption intention toward web ATM. The results are helpful for financial institutions to understand and to evaluate the user behavior toward internet banking service adoption. Show more

Keywords: Fuzzy analytic hierarchy process, case-based reasoning, web ATM, innovation adoption

DOI: 10.3233/JIFS-191408

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2869-2879, 2020

Authors: Dong, Hongwei | Yang, Liming

Article Type: Research Article

Abstract:  Symmetric loss functions are widely used in regression algorithms to focus on estimating the means. Huber loss, a symmetric smooth loss function, has been proved that it can be optimized with high efficiency and certain robustness. However, mean estimators may be poor when the noise distribution is asymmetric (even outliers caused heavy-tailed distribution noise) and estimators beyond the means are necessary. Under the circumstances, quantile regression is a natural choice which estimates quantiles instead of means through asymmetric loss functions. In this paper, an asymmetric Huber loss function is proposed to implement different penalty for overestimation and underestimation so as …to deal with more general noise. Moreover, a smooth truncated version of the proposed loss is introduced to enhance stronger robustness to outliers. Concave-convex procedure is developed in the primal space with the proof of convergence to handle the non-convexity of the involved truncated objective. Experiments are carried out on both artificial and benchmark datasets and robustness of the proposed methods are verified. Show more

Keywords: Support vector regression, training in the primal, robustness, asymmetric Huber loss, concave-convex procedure

DOI: 10.3233/JIFS-191429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2881-2892, 2020

Authors: Wu, Huaiguang | Xie, Pengjie | Zhang, Huiyi | Li, Daiyi | Cheng, Ming

Article Type: Research Article

Abstract: The chest X-ray examination is one of the most important methods for screening and diagnosing of many lung diseases. Diagnosis of pneumonia by chest X-ray is one of the common methods used by medical experts. However, the image quality of chest X-Ray has some defects, such as low contrast, overlapping organs and blurred boundary, which seriously affects detecting pneumonia in chest X-rays. Therefore, it has important medical value and application significance to construct a stable and accurate automatic detection model of pneumonia through a large number of chest X-ray images. In this paper, we propose a novel hybrid system for …detecting pneumonia from chest X-Ray image: ACNN-RF, which is an adaptive median filter Convolutional Neural Network (CNN) recognition model based on Random forest (RF). Firstly, the improved adaptive median filtering is employed to remove noise in the chest X-ray image, which makes the image more easily recognized. Secondly, we establish the CNN architecture based on Dropout to extract deep activation features from each chest X-ray image. Finally, we employ the RF classifier based on GridSearchCV class as a classifier for deep activation features in CNN model. It not only avoids the phenomenon of over-fitting in data training, but also improves the accuracy of image classification. During our experiment, the public chest X-ray image dataset used in the experiment contains 5863 images, which comprises 4265 frontal-view X-ray images of 1574 unique patients. The average recognition rate of pneumonia is up to 97% by the proposed ACNN-RF. The experimental results show that the ACNN-RF identification system is more effective than the previous traditional image identification system. Show more

Keywords: Chest X-ray, CNN, adaptive median filter, RF, image classification

DOI: 10.3233/JIFS-191438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2893-2907, 2020

Authors: Lei, Fan | Lu, Jianping | Wei, Guiwu | Wu, Jiang | Wei, Cun | Guo, Yanfeng

Article Type: Research Article

Abstract: In this paper, we provide the probabilistic linguistic multiple attribute group decision making (PL-MAGDM) with incomplete weight information. In such method, the linguistic information firstly is shifted into probabilistic linguistic information. For obtaining the weight information of the attribute, two optimization models are built on the basis of the basic idea of grey relational analysis (GRA), by which the attribute weights can be obtained. Then, the optimal alternative is obtained through calculating largest relative relational degree from the probabilistic linguistic positive ideal solution (PLPIS) which considers both the largest grey relational coefficient (GRC) from the PLPIS and the smallest GRC …form probabilistic linguistic negative ideal solution (PLNIS). Finally, a case study for waste incineration plants location problem is given to demonstrate the advantages of the developed methods. Show more

Keywords: multiple attribute group decision making (MAGDM), probabilistic linguistic term sets (PLTSs), GRA method, incomplete weight information, waste incineration plants

DOI: 10.3233/JIFS-191443

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2909-2920, 2020

Authors: Pirayesh, Pardis | Motameni, Homayun | Akbari, Ebrahim

Article Type: Research Article

Abstract: Fuzzy logic is a multi-valued concept, whose emergence in software sciences has eliminated 0 and 1 computations, putting them within an infinite space of [0,1]. This characteristic of fuzzy logic has resolved ambiguity in numerous previous problems. The sentence roles in Persian language were specified based on the fuzzy logic’s capability to resolve ambiguity. For that purpose, we first obtained the best classification for each defuzzifier, based on which a classified fuzzy was implemented. Nonetheless, the fuzzy system used in this research was classified based on statistical computations. To achieve the best classification, five defuzzification methods (Mean Of Max, Max …Of Membership, Largest Of Max, Smallest Of Max, and Central Average) competed in 16 roles each in five classes (different matrices). Finally, Mean of Max with a success rate of 64% proved to be a defuzzifier delivering the best output among 5 different defuzzification methods. Show more

Keywords: Fuzzy role, defuzzifier, terminology

DOI: 10.3233/JIFS-191447

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2921-2934, 2020

Authors: Shang, Bo | Du, Xingyu

Article Type: Research Article

Abstract: An intelligent decision analytic framework for dealing with complex decision-making risk system is presented and Bayesian network (BN) approach is utilized to evaluate the influence of multilevel uncertainty in various risks (e.g., social, natural, economic, intracompany risks) on decision-making deviation of Chinese hydropower corporations. The technique of fuzzy probability is approached to calculate intricate parameters to the question of inference learning through the sensitivity and influence power analysis, the results of back inference show that there exists the risk transformation mechanism from external uncertain risks (e.g., social risks, ecological environment factors) to hydropower corporations’ internal uncertainties closely relating to economic …uncertainties through strategic planning. The study concerning identification and intelligent analysis of uncertain risks in decision-making process illustrates the feasibility and validity of applying BN and its pragmatic implications on hydropower corporations strategic planning and guidance in operational management. Show more

Keywords: Chinese hydropower corporations, decision makers, decision-making risks, Bayesian network, triangular fuzzy numbers

DOI: 10.3233/JIFS-191469

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2935-2945, 2020

Authors: Shang, Bo | Huang, Taozhen | Du, Xingyu

Article Type: Research Article

Abstract: In a significant period of Chinese energy reformation to the point of expediting revolution in energy production and consumption, and promoting green low-carbon upgrading transformation of energy electricity, Chinese government has to implement the obligatory policy of renewable portfolio standards (RPS) with specific institutional provisions sternly. The renewable energy quotas in thermal power industry with carbon emission abatement constraints particularly have a latent impact on the behavior of thermal electricity producers, which is ineluctably involved in electricity connection of grid companies. To make clear the positive role in boosting investment in renewable energy generation in thermal power industry under mandatory …quotas requirements, we will utilize evolutionary game based on system dynamics (SD) to tackle with the sophisticated nexus among the government, thermal power producers and grid companies. We begin analysis of general evolutionary strategy stability in scenario ll by dynamically adjusting values of external variables of SD model to uncover pivotal variables affecting evolutionary strategy stability. Then in scenario I, the dynamic punishment structure consisting of cost elements to spark off the emulation of optimal manoeuvre selections of tripartite game agents is amended based on the simulation of vital variables affecting evolutionary strategy stability in scenario II. The significant conclusions provide decision-making support and management enlightenment for Chinese government to edge renewable energy generation capacity of thermal power producers and constrained degree of dynamic penalty for grid companies. Show more

Keywords: Renewable portfolio standards (RPS), China’s power market, Carbon abatement, Government regulation, evolutionary strategy stability, system dynamics

DOI: 10.3233/JIFS-191470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2947-2975, 2020

Authors: Anushiadevi, R. | Praveenkumar, Padmapriya | Rayappan, John Bosco Balaguru | Amirtharajan, Rengarajan

Article Type: Research Article

Abstract: Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was …based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images. Show more

Keywords: Reversible data hiding, pixel expansion, reversible data hiding in encrypted image, imperceptibility, homomorphic encryption

DOI: 10.3233/JIFS-191478

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2977-2990, 2020

Authors: Kaul, Sonam Devgan | Hatzinakos, Dimitrios

Article Type: Research Article

Abstract: In this work, we will be investigating, developing and implementing an intelligent RFID system in conjunction with a fuzzy data classification system, to greatly enhance and secure financial transactions and improve operational efficiency in the banking environment. The innovative part of this research is to provide an efficient solution to the challenge that may arise from the need to expertly and automatically match the profile of customer and banker and solve the vagueness in customer/banking profiling. Our proposal offers an expert, secure, efficient and comprehensive framework, methodology and its application in financial environments to develop customer to banker profile matching …and availability via an expert agent multi level fuzzy data classification system. Foremost, according to clients and banking staff members weighted attributes, exact match has been established according to highest degree of relevance by utilizing Matlab fuzzy inference system. Then, to communicate output of a match profile engine from one party to another, to show profiling effectiveness and to do implementation; secure, privacy preserving, and comprehensive intelligent RFID profiling authentication system has been designed and verified by Scyther tool. Show more

Keywords: Authentication system, fuzzy inference system, intelligent system, matlab, profiling system, RFID, Scyther

DOI: 10.3233/JIFS-191480

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2991-3010, 2020

Authors: Munirathinam, T. | Ganapathy, Sannasi | Kannan, Arputharaj

Article Type: Research Article

Abstract: Rapid introduction of new diseases and the severity improvement of existing dead diseases due to the bad food habits and lacking of awareness over the health conscious food items those are available in the market. The Internet of Things (IoT) gets more attention for reducing the disease severity by knowing the current status of their disease according to the dynamic inputs of human body through IoT devices today. Moreover, the combination of IoT and cloud computing technologies are playing major roles in e-health services. In this scenario, security is a major issue in the process of data storage and communication. …For this purpose, we propose a new e-healthcare system for monitoring the dead disease level by using the technologies such as IoT and Cloud with the help of deep learning approach and fuzzy rules with temporal features. In this system, the medical data is retrieved from various located patients who are utilizing the e-healthcare assisting devices. First, the retrieved and encrypted data is stored in cloud by applying a newly proposed secured cloud storage algorithm. Second, the stored data can be retrieved the data as original data by applying the decryption process. Third, a new cloud framework is introduced for predicting the status of heart beat rates and diabetes levels by using the medical data that is created by applying the UCI Repository dataset. In addition, a new deep learning approach which applies the Convolutional Neural Network for predicting the disease severity. The experimental results are obtained by conducting various experiments for the proposed model by using the dataset and the hospital patient records. The proposed model results outperforms the available disease prediction systems in terms of prediction accuracy. Show more

Keywords: Internet of things (IoT), CNN, cryptography, encryption, decryption, elliptic curve cryptography and e-healthcare.

DOI: 10.3233/JIFS-191490

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3011-3023, 2020

Authors: Işık, Hüseyin | Sezen, Muzeyyen Sangurlu

Article Type: Research Article

Abstract: In this work, we prove a new fixed point theorem in the setting fuzzy metric spaces. The fuzzy metric space considered here is assumed to have two partial orders defined on it. We introduce a new approach to the existence of a fixed point of a function satisfying the two constraint inequalities. An example is included which illustrates new results of this paper. Moreover, an application of our result to the study of integral equations is provided.

Keywords: Common fixed points, constraint inequalities, G-complete fuzzy metric spaces, partial order

DOI: 10.3233/JIFS-191521

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3025-3032, 2020

Authors: Wang, Zecong | Parvin, Hamid | Qasem, Sultan Noman | Tuan, Bui Anh | Pho, Kim-Hung

Article Type: Research Article

Abstract: A bad partition in an ensemble will be removed by a cluster ensemble selection framework from the final ensemble. It is the main idea in cluster ensemble selection to remove these partitions (bad partitions) from the selected ensemble. But still, it is likely that one of them contains some reliable clusters. Therefore, it may be reasonable to apply the selection phase on cluster level. To do this, a cluster evaluation metric is needed. Some of these metrics have been recently introduced; each of them has its limitations. The weak points of each method have been addressed in the paper. Subsequently, …a new metric for cluster assessment has been introduced. The new measure is named Balanced Normalized Mutual Information (BNMI) criterion. It balances the deficiency of the traditional NMI-based criteria. Additionally, an innovative cluster ensemble approach has been proposed. To create the consensus partition considering the elected clusters, a set of different aggregation-functions (called also consensus-functions) have been utilized: the ones which are based upon the co-association matrix (CAM), the ones which are based on hyper graph partitioning algorithms, and the ones which are based upon intermediate space. The experimental study indicates that the state-of-the-art cluster ensemble methods are outperformed by the proposed cluster ensemble approach. Show more

Keywords: Cluster ensembles, enhanced stability, extended-EAC, CAM, cluster evaluation

DOI: 10.3233/JIFS-191531

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3033-3055, 2020

Authors: Jamwal, Prashant K. | Hussain, Shahid

Article Type: Research Article

Abstract: Globalization of business around the world has turned individual firms into groups of collaborating business units whereby companies do not operate in isolation but function as integral part of big supply chain networks (SCN). Organization of SCN is quite complex as they operate with uncertainty in demands and operations. However, supply chain networks are required to be optimized in order to reduce the overall supply chain cost and increase service levels. Since these objectives are normally conflicting and incommensurable, instead of a singular solution, it is preferred to obtain a set of equitable solutions which is commonly referred to as …set of Pareto optimal solutions. Subsequently, a suitable solution can be chosen by the user from the set of equitable solutions. In the present research, a multi-echelon SCN problem is formulated and two important objectives are identified. It is desired to minimize the total cost of supply chain network and at the same time maximize customer service level in terms of supply to demand ratio. Simultaneous optimization of these objectives has been carried out using an evolutionary algorithm (EA) called NSGA-II, which works with population of SCN solutions and is more likely to provide set of globally optimized solutions. However, at the conclusion of optimization, user needs to select a final solution from the Pareto optimal set of solutions after careful analysis. Existing approaches to carry out such analysis are complex and time consuming. We propose a novel method involving fuzzy logic in this research by which fuzzy indices corresponding to each of the solutions in the Pareto Front (PF) are obtained. Fuzzy indices of all the Pareto optimal SCN solutions are later compared to reach to a final solution from the Pareto optimal set. Show more

Keywords: Evolutionary algorithms, fuzzy logic, pareto optimal solutions, supply chain networks

DOI: 10.3233/JIFS-191534

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3057-3066, 2020

Authors: Yang, Hai-Long | Zhou, Jia-Jia

Article Type: Research Article

Abstract: By combining interval-valued Pythagorean fuzzy sets with rough sets, the interval-valued Pythagorean fuzzy rough set model is first constructed in this paper. The connections between special interval-valued Pythagorean fuzzy relations and interval-valued Pythagorean fuzzy approximation operators are established subsequently. Then, we study the axiomatic characterizations of interval-valued Pythagorean fuzzy lower and upper approximation operators. Different axiom sets of interval-valued Pythagorean fuzzy set-theoretic operators ensure the existence of different types of interval-valued Pythagorean fuzzy relations producing the same operators. Finally, we give an example to illustrate the practical application of the newly proposed model.

Keywords: Interval-valued pythagorean fuzzy sets, interval-valued pythagorean fuzzy relations, interval-valued pythagorean fuzzy rough sets, axiomatic characterizations

DOI: 10.3233/JIFS-191539

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3067-3084, 2020

Authors: Nawar, A.S. | El-Bably, M.K. | El-Atik, Abd El Fattah

Article Type: Research Article

Abstract: Covering-based rough sets are important generalizations of the classical rough sets of Pawlak. In this paper, by means of j -neighborhoods, complementary j -neighborhoods and j -adhesions, we build some new different types of j -covering approximations based rough sets and study related properties. Also, we explore the relationships between the considered j -covering approximations and investigate the properties of them. Using different neighborhoods, some different general topologies are generated as topologies induced from a binary relation. Finally, an interesting application of the new types of covering-based rough sets to the rheumatic fever is given.

Keywords: Covering-based rough sets, approximation space, topology, neighborhood, complementary neighborhood

DOI: 10.3233/JIFS-191542

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3085-3098, 2020

Authors: Bagheri, M. | Ebrahimnejad, A. | Razavyan, S. | Hosseinzadeh Lotfi, F. | Malekmohammadi, N.

Article Type: Research Article

Abstract: A transportation problem basically deals with the problem which aims to minimize the total transportation cost or maximize the total transportation profit of distributing a product from a number of sources or origins to a number of destinations. While, in general, most of the real life applications are modeled as a transportation problem (TP) with the multiple, conflicting and incommensurate objective functions. On the other hand, for some reason such as shortage of information, insufficient data or lack of evidence, the data of the mentioned problem are not always exact but can be fuzzy. This type of problem is called …fuzzy multi-objective transportation problem (FMOTP). There are a few approaches to solve the FMOTPs. In this paper, a new fuzzy DEA based approach is developed to solve the Fully Fuzzy MOTPs (FFMOTPs) in which, in addition to parameters of the MOTPs, all of the variables are considered fuzzy. This approach considers each arc in a FFMOTP as a decision making unit which produces multiple fuzzy outputs using the multiple fuzzy inputs. Then, by using the concept of the common set of weights (CSW) in DEA, a unique fuzzy relative efficiency is defined for each arc. In the following, the unique fuzzy relative efficiency is considered as the only attribute for the arcs. In this way, a single objective fully fuzzy TP (FFTP) is obtained that can be solved using the existing standard algorithms for solving this kind of TPs. A numerical example is provided to illustrate the developed approach. Show more

Keywords: Fuzzy multi-objective transportation problem, data envelopment analysis, fuzzy arithmetic, common set of weights

DOI: 10.3233/JIFS-191560

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3099-3124, 2020

Authors: Wei, Guiwu | He, Yan | Lei, Fan | Wu, Jiang | Wei, Cun | Guo, Yanfeng

Article Type: Research Article

Abstract: In recent years, with the increased voice for protecting the environment by the people all over the world, the governments also have actively adopted more and more measures to further promote environmental conservation and sustainable development. Traditional procurement approaches have not well updated to the current needs of the society, especially for the retail industry which is in relation to the national economy due to numerous products and different suppliers being involved. Therefore, the need for green procurement is more important. The qualified green supplier selection is the core of green procurement, which is the utmost importance in the business …competition throughout the supply chain in today’s strong business competition. Thus, in order to obtain the optimal green supplier, integration of Entropy weights and multi-attributive border approximation area comparison (MABAC) under uncertain probabilistic linguistic sets (UPLTSs) has offered a novel integrated model, in which information Entropy is utilized for calculating objective weights with UPLTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems. Show more

Keywords: Multiple attribute group decision making (MAGDM), uncertain probabilistic linguistic term sets (UPLTSs), MABAC method, entropy method, green supplier selection

DOI: 10.3233/JIFS-191584

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3125-3136, 2020

Authors: Bera, Sanchari | Pal, Madhumangal

Article Type: Research Article

Abstract: In this paper, an unprecedented kind of fuzzy graph designated as m -polar interval valued fuzzy graph (m -PIVFG) is defined. Complement of the m -PIVFG open and closed neighborhood degrees of m -PIVFG are discussed. The other algebraic properties such as density, regularity, irregularity of the m -PIVFG are investigated. Moreover, some basic results on regularity and irregularity of m -PIVFG are proved. Free nodes and busy nodes of m -PIVFG is explored with some basic theorems and examples. Lastly, an application of m -PIVFG is described.

Keywords: m-polar interval-valued fuzzy graph, balanced m-PIVFG, regularity and irregularity in m-PIVFG, density of m-PIVFG, free and busy nodes in m-PIVFG

DOI: 10.3233/JIFS-191587

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3137-3150, 2020

Authors: Li, Xiaoping | Tao, Yujie | Li, Yanhong

Article Type: Research Article

Abstract: A polygonal fuzzy numbers can describe fuzzy information by means of finite ordered real numbers. It not only overcomes the complexity of traditional fuzzy number operations, but also keeps some good properties of trapezoidal fuzzy numbers, and it can approximate general fuzzy numbers with arbitrary precision. In this paper, a weighted arithmetic average operator is defined by the ordered representation and its operations of the polygonal fuzzy numbers, and a new Euclidean distance for measuring the polygonal fuzzy numbers is given. Secondly, in view of cost attribute and benefit attributes, the polygonal fuzzy decision matrix is normalized, and the weighted …Euclidean distance is used to solve the positive (negative) ideal solution and the relative closeness of the decision matrix, and then a new decision method is given. Finally, the effectiveness of the proposed decision-making method is illustrated by an example of the evaluation of logistics companies by shopping websites. Show more

Keywords: Polygonal fuzzy number, ordered representation, Euclidean distance, positive (negative) ideal solution, multiple attribute decision making

DOI: 10.3233/JIFS-191588

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3151-3166, 2020

Authors: Sinha, Bam Bahadur | Dhanalakshmi, R.

Article Type: Research Article

Abstract: In the current era of big data, the recommender system aspires to provide users with a tailored set of personalized items from a pool of a large population. The most popular collaborative filtering system performs this information filtering process by computing similarity among users or items. This paper proposes a similarity metric that comprises of weights and values. Values are calculated by considering the matching set of users for which similarity is to be computed. The optimal values of weights are decided using an upgraded form of the Crow Search Algorithm (CSA). The exploration and exploitation stability of CSA is …improvised by making use of Levy flight diffusion, adaptive operator adjustment, and event factor. The performance of the implemented metaheuristic approach is validated on Jester, MovieLens 100K, and MovieLens 1M dataset. Comparative analysis of proposed model against several other traditional metaheuristic based personalization systems reveal that our model is less delicate to the dimension of datasets and it also presents exceptional refinement in terms of prediction complexity and accuracy. Show more

Keywords: Collaborative filtering, similarity, crow search algorithm, optimization, movielens, jester

DOI: 10.3233/JIFS-191594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3167-3182, 2020

Authors: Li, Jieya | Yang, Liming

Article Type: Research Article

Abstract: The classical principal component analysis (PCA) is not sparse enough since it is based on the L 2 -norm that is also prone to be adversely affected by the presence of outliers and noises. In order to address the problem, a sparse robust PCA framework is proposed based on the min of zero-norm regularization and the max of L p -norm (0 < p  ≤ 2) PCA. Furthermore, we developed a continuous optimization method, DC (difference of convex functions) programming algorithm (DCA), to solve the proposed problem. The resulting algorithm (called DC-LpZSPCA) is convergent linearly. In addition, when choosing different p …values, the model can keep robust and is applicable to different data types. Numerical simulations are simulated in artificial data sets and Yale face data sets. Experiment results show that the proposed method can maintain good sparsity and anti-outlier ability. Show more

Keywords: Principal component analysis, sparseness, robustness, zero-norm, DC programming, face reconstruction

DOI: 10.3233/JIFS-191617

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3183-3193, 2020

Authors: Mehrani, Mohammad | Attarzadeh, Iman | Hosseinzadeh, Mehdi

Article Type: Research Article

Abstract: Wireless Body Area Networks (WBANs) have been introduced as a useful way in controlling health status of the monitored patients, during recent years. Each WBAN includes a number of biosensors attached to the patient’s body, collecting his vital sign features and communicating them to the coordinator to make appropriate decisions. Managing energy consumption of biosensors and continuous monitoring of the patients are two main issues in WBANs. Hence, denoting efficient sampling frequency of biosensors is very important in WBANs. In this paper, we propose a scheme which aims at determining and forecasting sampling rate of active biosensors in WBANs. In …this regard, from the first round until a certain round, the sampling rate of biosensors would be determined. Accordingly, we introduce our modified Fisher test, develop spline interpolation method and introduce three main parameters. These parameters are information of patient’s activity, patient’s risk and pivot biosensor’s value. Then, by employing mentioned parameters in addition to the introduced statistical and mathematical based strategies, the sampling rate of active biosensors in the next round would be determined at the end of each entire round. By reaching a pre-denoted round, the sampling rate of biosensors would be predicted through forecasting methods. For this purpose, we develop two machine learning based techniques namely Adaptive Neuro Fuzzy Inference System (ANFIS) and Long Short Term Memory (LSTM). For estimation our approaches we simulate them in MATLAB R2018b software. Simulation results demonstrate that our methods can decrease the number of communicated data by 81%, reduce energy expenditure of biosensors by 73% and forecast the sampling rate of biosensors in the future rounds with 97% accuracy and 2.2753 RMSE. Show more

Keywords: WBANs, sampling rate determining, sampling rate forecasting, energy efficiency, overhead data, modified fisher test, spline, ANFIS, LSTM.

DOI: 10.3233/JIFS-191622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3195-3227, 2020

Authors: Bai, Nan | Chen, Guangzhu | Hou, Rui | Ying, Feng

Article Type: Research Article

Abstract: With the sustainable development of mobile communication technology and the increasing demand for indoor services, Location-based Service (LBS) is attracting more and more attention. Determining the mobile target’s location is a core problem of LBS. The traditional WiFi signal fingerprint-based positioning technology mainly determines the location information of the mobile target by received RSS, which has high real-time positioning but low positioning accuracy. The fingerprint-based positioning technology using image mainly determines the location information of the mobile target by matching the features of the foreground images, which has the high positioning accuracy but low real-time positioning. This paper presents an …indoor positioning method fusing information of the WiFi signal and RGB image to improve the positioning performance. The WiFi signal is transformed into the W-image according to indoor space and correction radius parameters, then the W-image and RGB image information are fused with LBP feature by the uniform-LBP algorithm. A fusion positioning model based on the sparse representation is established and solved using Lasso and BPDN positioning method. The positioning methods are tested in manufacturing workshop, and the experimental results show that the proposed method can reduce the complexity of the positioning method and achieve the higher positioning accuracy under same conditions. Show more

Keywords: Indoor positioning, WiFi signal, RGB image, manufacturing workshop, sparse representation

DOI: 10.3233/JIFS-191647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3229-3240, 2020

Authors: Xu, Xinggui | Yang, Ping | Ran, Bing | Xian, Hao | Liu, Yong

Article Type: Research Article

Abstract: The tough challenges of object recognition in long-distance scene involves contour shape deformation invariant features construction. In this work, an effective contour shape descriptor integrating critical points structure and Scale-invariant Heat Kernel Signature (SI-HKS) is proposed for long-distance object recognition. We firstly propose a general feature fusion model. Then, we capture the object contour structure feature with Critical-points Inner-distance Shape Context (CP-IDSC). Meanwhile, we pull-in the SI-HKS for capturing the local deformation-invariant properties of 2D shape. Based on the integration of the above two feature descriptors, the fusion descriptor is compacted by mapping into a low dimensional subspace using the …bags-of-features, allowing for an efficient Bayesian classifier recognition. The extensive experiments on synthetic turbulence-degraded shapes and real-life infrared image show that the proposed method outperformed other compared approaches in terms of the recognition precision and robustness. Show more

Keywords: Imaging through turbulent media, shape invariant descriptor, heat kernel signature, shape context, contour shape recognition

DOI: 10.3233/JIFS-191649

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3241-3257, 2020

Authors: Shahsavari-Pour, Nasser | Bahram-Pour, Najmeh | Kazemi, Mojde

Article Type: Research Article

Abstract: The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective …firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems. Show more

Keywords: Fuzzy optimization, location and routing, firefly algorithm, NSGAII algorithm, reliability, failure

DOI: 10.3233/JIFS-191654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3259-3273, 2020

Authors: Tianhe, Yin | Mahmoudi, Mohammad Reza | Qasem, Sultan Noman | Tuan, Bui Anh | Pho, Kim-Hung

Article Type: Research Article

Abstract: A lot of research has been directed to the new optimizers that can find a suboptimal solution for any optimization problem named as heuristic black-box optimizers. They can find the suboptimal solutions of an optimization problem much faster than the mathematical programming methods (if they find them at all). Particle swarm optimization (PSO) is an example of this type. In this paper, a new modified PSO has been proposed. The proposed PSO incorporates conditional learning behavior among birds into the PSO algorithm. Indeed, the particles, little by little, learn how they should behave in some similar conditions. The proposed method …is named Conditionalized Particle Swarm Optimization (CoPSO). The problem space is first divided into a set of subspaces in CoPSO. In CoPSO, any particle inside a subspace will be inclined towards its best experienced location if the particles in its subspace have low diversity; otherwise, it will be inclined towards the global best location. The particles also learn to speed-up in the non-valuable subspaces and to speed-down in the valuable subspaces. The performance of CoPSO has been compared with the state-of-the-art methods on a set of standard benchmark functions. Show more

Keywords: Swarm intelligence, black-box optimizer, particle swarm optimization, adaptive conditionalized particle swarm optimization

DOI: 10.3233/JIFS-191685

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3275-3295, 2020

Authors: Sinha, Keshav | Priya, Annu | Paul, Partha

Article Type: Research Article

Abstract: Cloud has become one of the most demanding services for data storage. On another hand, the security of data is one of the challenging tasks for Cloud Service Provider (CSP). Cryptography is one of the ways for securing the storage data. Cryptography is not a new approach instead of the efficient utilization of cryptographical algorithms is greatly needed. In this work, we proposed a Secure Hidden Layer (SHL) and Application Programming Interface (API) for data encryption. The SHL is consisting of two major modules (i) Key Management Server (KMS) and (ii) Share Holder Server (SHS) which is used for storing …and sharing of cryptographic key. For this purpose, we proposed a server-side encryption algorithm, which is based on the asymmetric algorithm (RSA and CRT) for providing end-to-end security of multimedia data. The experimental results of text and video are evidence that the size of file is not much affected after the encryption and effectively stored at Cloud Storage Server (CSS). The parameters like ciphertext size, encryption time and throughput are considered for performance evaluation of the proposed encryption technique. Show more

Keywords: Secure hidden layer (SHL), key management server (KMS), share holder server (SHS), cloud service provider (CSP), chinese remainder theorem (CRT), cloud storage server (CSS)

DOI: 10.3233/JIFS-191687

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3297-3314, 2020

Authors: Wei, Guiwu | He, Yan | Lei, Fan | Wu, Jiang | Wei, Cun

Article Type: Research Article

Abstract: In recent years, ecological problems have become increasingly serious which are forcing people to give up the past high investment, high consumption and high emission development to promote green growth, implement the green new deal and pay attention to green supply chain research and practice. Therefore, in order to attach great importance to the economic and environmental benefits, enterprises should implement green supply chain and “green” change which has become the trend and urgent. Thus, in order to obtain an optimal green supplier, integration of combined weights and multi-attributive border approximation area comparison (MABAC) under probabilistic uncertain linguistic sets (PULTSs) …has offered a novel integrated model, in which information entropy is utilized for calculating objective weights with PULTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems. Show more

Keywords: Multiple attribute group decision making (MAGDM), probabilistic uncertain linguistic term sets (PULTSs), MABAC method, entropy method, combined weights, green supplier selection

DOI: 10.3233/JIFS-191688

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3315-3327, 2020

Authors: Akram, Muhammad | Muhammad, Ghulam | Allahviranloo, Tofigh | Hussain, Nawab

Article Type: Research Article

Abstract: The aim of this work is to solve the linear system of equations using LU decomposition method in bipolar fuzzy environment. We assume a special case when the coefficient matrix of the system is symmetric positive definite. We discuss this point in detail by giving some numerical examples. Moreover, we investigate m  × n inconsistent bipolar fuzzy matrix equation and find the least square solution of the inconsistent bipolar fuzzy matrix using the generalized inverse matrix theory. The existence of the strong bipolar fuzzy least square solution of the inconsistent bipolar fuzzy matrix is discussed. In the end, a numerical …example is presented to illustrate our proposed method. Show more

Keywords: LU decomposition method, symmetric positive definite matrix, inconsistent bipolar fuzzy matrix equations, bipolar fuzzy least square solution

DOI: 10.3233/JIFS-201187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3329-3349, 2020

Authors: Liu, Peide | Ali, Zeeshan | Mahmood, Tahir

Article Type: Research Article

Abstract: The information measures (IMs) of complex fuzzy information are very useful tools in the areas of machine learning and decision making. In some multi-attribute group decision making (MAGDM) problems, the decision makers can make a decision mostly according to IMs such as similarity measures (SMs), distance measures (DIMs), entropy measures (EMs) and cross-entropy measures (C-EMs) in order to choose the best one. However, the relation between C-EMs and DIMs in the environment of complex fuzzy sets (CFSs) has not been developed and verified. In this manuscript, the notions of DIMs and C-EMs in the environment of CFSs are investigated and …the relation between DIMs and EMs in the environment of CFSs is also discussed. The complex fuzzy discrimination measures (CFDMs), the complex fuzzy cross-entropy measures (CFC-EMs), and the symmetry complex fuzzy cross-entropy measures (SCFC-EMs) are proposed. We also examined that the C-EMs satisfied all the conditions of DIMs, and finally proved that C-EMs including CFC-EMs were also a DIMs. In last, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods. Show more

Keywords: Fuzzy sets, complex fuzzy sets, cross-entropy measures, distance measures

DOI: 10.3233/JIFS-191718

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3351-3374, 2020

Authors: Javed, Shazia | Ahmad, Noor Atinah

Article Type: Research Article

Abstract: Despite its low computational cost, and steady state behavior, some well known drawbacks of the least means squares (LMS) algorithm are: slow rate of convergence and unstable behaviour for ill conditioned autocorrelation matrices of input signals. Several modified algorithms have been presented with better convergence speed, however most of these algorithms are expensive in terms of computational cost and time, and sometimes deviate from optimal Wiener solution that results in a biased solution of online estimation problem. In this paper, the inverse Cholesky factor of the input autocorrelation matrix is optimized to pre-whiten input signals and improve the robustness of …the LMS algorithm. Furthermore, in order to have an unbiased solution, mean squares deviation (MSD) is minimized by improving convergence in misalignment. This is done by regularizing step-size adaptively in each iteration that helps in developing a highly efficient optimal preconditioned regularized LMS (OPRLMS) algorithm with adaptive step-size. Comparison of OPRLMS algorithm with other LMS based algorithms is given for unknown system identification and noise cancelation from ECG signal, that results in preference of the proposed algorithm over the other variants of LMS algorithm. Show more

Keywords: Optimal Cholesky factor, regularization, variable step-size, preconditioning

DOI: 10.3233/JIFS-191728

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3375-3385, 2020

Authors: Singh, Ravindra | Khatoon, Shahida | Chaudhary, Himanshu | Pandey, Ashish

Article Type: Research Article

Abstract: Gimballed sensor system is a precision electromechanical assembly designed primarily to isolate the optical system from disturbances induced by the operating environment. This paper gives an insight to the design and development of gimballed sensor system for Line of Sight (LOS) stabilization of an electro-optical tracking and pointing system. Initially kinematic equations are formulated to establish a relationship between LOS angle and applied torque. This relationship is used to obtain nested loop transfer function model. First, the parameters of the proposed assembly are determined through experimentation & rigorous analysis process, and then conventional control design methodology is adopted for controller …configuration design for current and rate loop. The frequency response analysis of the designed LOS stabilization model with conventional controller is done in simulation and the obtained results are verified experimentally against angular disturbances in real time scenario. Further, Based on prior qualitative information about system dynamics and linguistic performance criteria, a fuzzy logic controller of mamdani type with simplified rule set is developed with an objective to improve the disturbance attenuation and command response performance of designed system irrespective of angular disturbances due to platform vibrations, model uncertainties and mass imbalance in gimbal assembly. Both the Fuzzy logic simulation model and conventional model are tested based on critical performance characteristics such as stability of the loop, responsiveness of the loop and insensitivity to disturbances. Finally, the comparative analysis suggests that, although both the control configuration satisfies the required accuracy, Fuzzy logic control certainly improvised the performance of the gimballed sensor system and hence can be very effective for more precise pointing, tracking and stabilization application. Show more

Keywords: Proportional integral (PI) compensation, fuzzy logic control, jitter attenuation, gimballed electro-optical system, tracking and pointing

DOI: 10.3233/JIFS-191735

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3387-3399, 2020

Authors: Peng, Yong | Zhang, Leijie | Kong, Wanzeng | Qin, Feiwei | Zhang, Jianhai

Article Type: Research Article

Abstract: Subspace learning aims to obtain the corresponding low-dimensional representation of high dimensional data in order to facilitate the subsequent data storage and processing. Graph-based subspace learning is a kind of effective subspace learning methods by modeling the data manifold with a graph, which can be included in the general spectral regression (SR) framework. By using the least square regression form as objective function, spectral regression mathematically avoids performing eign-decomposition on dense matrices and has excellent flexibility. Recently, spectral regression has obtained promising performance in diverse applications; however, it did not take the underlying classes/tasks correlation patterns of data into consideration. …In this paper, we propose to improve the performance of spectral regression by exploring the correlation among classes with low-rank modeling. The newly formulated low-rank spectral regression (LRSR) model is achieved by decomposing the projection matrix in SR by two factor matrices which were respectively regularized. The LRSR objective function can be handled by the alternating direction optimization framework. Besides some analysis on the differences between LRSR and existing related models, we conduct extensive experiments by comparing LRSR with its full rank counterpart on benchmark data sets and the results demonstrate its superiority. Show more

Keywords: Low-rankness, spectral regression, matrix factorization, subspace learning, classification

DOI: 10.3233/JIFS-191752

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3401-3412, 2020

Authors: Tan, Ruipu | Zhang, Wende

Article Type: Research Article

Abstract:  Trapezoidal fuzzy neutrosophic decision making plays an important role in decision-making processes with uncertain, indeterminate, and inconsistent information. In this paper, we propose a new multi-attribute decision-making method based on decision-making trial and evaluation laboratory (DEMATEL), fuzzy distance, and linear assignment method (LAM), and we express evaluation values as the trapezoidal fuzzy neutrosophic numbers (TrFNNs). First, attribute weights are obtained using the DEMATEL method and the new fuzzy distance of TrFNNs based on graded mean integration representation is defined. Then, alternatives are ranked using the LAM in operations research. In addition, we make two comparative analyses in the end to …illustrate the feasibility and rationality of our method. Finally, an illustrative example about typhoon disaster assessment is presented to show the advantages of the proposed method. Show more

Keywords: Multiple attribute decision making, trapezoidal fuzzy neutrosophic set, DEMATEL, fuzzy distance, LAM, typhoon disaster evaluation

DOI: 10.3233/JIFS-191758

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3413-3439, 2020

Authors: Huang, Li | Wu, Jian-Zhang | Beliakov, Gleb

Article Type: Research Article

Abstract: MCCPI (Multiple Criteria Correlation Preference Information) is a kind of 2 dimensional decision preference information obtained by pairwise comparison on the importance and interaction of decision criteria. In this paper, we introduce the nonadditivity index to replace the Shapley simultaneous interaction index and construct an undated MCCPI based decision scheme. We firstly propose a diagram to help decision maker obtain the nonadditivity index type MCCPI, then establish transform equations to normalize them into desired capacity and finally adopt a random generation MCCPI based comprehensive decision aid algorithm to explore the dominance relationships and creditable ranking orders of all decision alternatives. …An illustrative example is also given to demonstrate the feasibility and effectiveness of the proposed decision scheme. It’s shown that based on some good properties of nonadditivity index in practice, the updated MCCPI model can deal with the internal interaction among decision criteria with relatively less model construction and calculation effort. Show more

Keywords: Multiple criteria decision analysis, capacity, fuzzy measure, nonadditivity index, interaction index

DOI: 10.3233/JIFS-191789

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3441-3452, 2020

Authors: Kamaruzaman, Nurzahara Atika | Omar, Mohd

Article Type: Research Article

Abstract: In practice, the demand for a fresh product depends on how fresh it is, therefore, it is important to take expiration date into consideration as it is a key to determine the freshness level of any perishable items. Furthermore, based on marketing and economic theory, selling price plays a crucial role in influencing the demand. Also, a higher inventory level may enhance the profit as it encourages consumers to buy more. Since the demand for fresh product declines over time, markdown policy is offered after some time to increase the demand and profit while reducing the inventory. For this demand …function, it may be profitable to maintain a high stock level and the zero ending inventory is relaxed to non-zero ending inventory. Salvage value is incorporated into the deteriorating units. Using differential equations, we propose an economic order quantity model which demand dependent on freshness-expiration date, price and inventory level under markdown policy. We also demonstrate the relationship between markdown time and the annual total profit. Numerical example and sensitivity analysis are used to illustrate the effectiveness of the model. Show more

Keywords: Inventory control, perishable items, expiration date, markdown policy, pricing strategy

DOI: 10.3233/JIFS-191794

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3453-3461, 2020

Authors: Ji, Fujiao | Zhao, Zhongying | Zhou, Hui | Chi, Heng | Li, Chao

Article Type: Research Article

Abstract: Heterogeneous information networks are widely used to represent real world applications in forms of social networks, word co-occurrence networks, and communication networks, etc. However, It is difficult for traditional machine learning methods to analyze these networks effectively. Heterogeneous information network embedding aims to convert the network into low dimensional vectors, which facilitates the following tasks. Thus it is receiving tremendous attention from the research community due to its effectiveness and efficiency. Although numerous methods have been present and applied successfully, there are few works to make a comparative study on heterogeneous information network embedding, which is very important for developers …and researchers to select an appropriate method. To address the above problem, we make a comparative study on the heterogeneous information network embeddings. Specifically, we first give the problem definition of heterogeneous information network embedding. Then the heterogeneous information networks are classified into four categories from the perspective of network type. The state-of-the-art methods for each category are also compared and reviewed. Finally, we make a conclusion and suggest some potential future research directions. Show more

Keywords: heterogeneous information network, network embedding, network representation learning, social network analysis

DOI: 10.3233/JIFS-191796

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3463-3473, 2020

Authors: Shahsavari-Pour, Nasser | Mohammadi-Andargoli, Hamed | Bahram-Pour, Najmeh

Article Type: Research Article

Abstract: The purpose of this paper is to introduce a new meta-heuristic algorithm and apply this for solving a multi-objective flexible job-shop scheduling problem. The name of this algorithm is Cosmogony (CA). This algorithm has inspired by the ecosystem process of creatures and their environment. For a better understanding, we make an effort to apply the concepts of the meta-heuristic algorithms up to a possible extent. This algorithm identifies local optimal points during the self-search process of problem-solving. Initial creatures have been generated randomly in a certain number. This algorithm incorporates many features of the other algorithms in itself. So that …to prove the ability and efficiency of CA, a flexible job-shop scheduling problem has surveyed. This problem is in a Non-resumable situation with maintenance activity constraints in a two-time fixed and non-fixed state. The algorithm performance is evaluated by numerical experiments. The result has shown the proposed approach is more efficient and appropriate than the other methods. It also has high power in the searching process in the feasible region of the multi-objective flexible job-shop scheduling problem and high converge power. Show more

Keywords: Cosmogony algorithm, meta-heuristic algorithms, flexible job shop scheduling problem, multi-objective optimization

DOI: 10.3233/JIFS-191839

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3475-3501, 2020

Authors: Wang, Guijun | Zhou, Jie

Article Type: Research Article

Abstract: The polygonal fuzzy set is an effective tool to express a class of fuzzy information with the help of finite ordered real numbers. It can not only guarantee the closeness of arithmetic operation of the polygonal fuzzy sets, but also has good linearity and intuitiveness. Firstly, the concept of the n -intuitionistic polygonal fuzzy set (n -IPFS) is proposed based on the intuitionistic fuzzy set and the polygonal fuzzy set. The ordered representation and arithmetic operation of n -IPFS are given by an example. Secondly, a new aggregation method for multi attribute fuzzy information is given based on the n …-IPFS operations and the weighted arithmetic average operator, and the ranking criteria of n -IPFS are obtained by using the score function and the accuracy function. Finally, a new group decision making method is proposed for urban residents to choose the livable city problem based on the decision matrix of the n -IPFS, and the effectiveness of the proposed method is explained by an actual example. Show more

Keywords: Polygonal fuzzy set, n-intuitionistic polygonal fuzzy set (n-IPFS), ordered representation, aggregation operator, score function, group decision making

DOI: 10.3233/JIFS-191844

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3503-3518, 2020

Authors: Deng, Xue | Chen, Chuangjie

Article Type: Research Article

Abstract: The purpose of this paper is to solve the portfolio selection problem when historical data are unavailable. In this paper, the problem is viewed as a multi-criteria decision making (MCDM) problem under intuitionistic fuzzy circumstances, and the prospect theory is utilized to reflect decision makers’ psychological state, which is always bounded rational. Therefore, a new approach to solve MCDM problems is presented based on the following improvements. (a) The entropy-weighted method with extreme data resistance is proposed instead of weight function to deal with the weight of criteria, because weight stands for the decision maker’s preference of criteria rather than …objective probability and should not be distorted. (b) A new entropy-weighted method with confidence degree is presented, which can not only describe the uncertainty of information each criterion provides but also reflect the decision maker’s confidence in the information. (c) To reduce the interference from extreme data, the median is selected as reference point instead of mean or extreme value. (d) Based on the distance measure, the intuitionistic fuzzy prospect value function is presented to capture decision makers’ psychological state. Finally, a novel model with prospect value constraint and risk preference is constructed to allocate investment ratios. For our proposed method and model, two numerical applications are given to verify their validity and the sensitivity analysis is carried out to illustrate their practical significance. Show more

Keywords: Portfolio selection, intuitionistic fuzzy set, prospect theory, entropy-weighted method, distance measure

DOI: 10.3233/JIFS-191848

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3519-3543, 2020

Authors: Bernal, Emer | Castillo, Oscar | Soria, José | Valdez, Fevrier

Article Type: Research Article

Abstract: In this paper we present a modification based on generalized type-2 fuzzy logic to an algorithm that is inspired on the movement of large masses of stars and their attractive force in the universe, known as galactic swarm optimization (GSO). The modification consists on the dynamic adjustment of parameters in GSO using type-1 and type-2 fuzzy logic. The main idea of the proposed approach is the application of fuzzy systems to dynamically adapt the parameters of the GSO algorithm, which is then applied to parameter optimization of the membership functions of the bar and ball fuzzy controller. The experimentation was …carried out using the original GSO algorithm, and the type-1 and type-2 fuzzy variants of GSO. In addition a disturbance was added to the bar and ball fuzzy controller plant to be able to validate the effectiveness of the proposed approach in optimizing fuzzy controllers. A formal comparison of results is performed with statistical tests showing that GSO with generalized type-2 fuzzy logic is the best method for optimizing the fuzzy controller. Show more

Keywords: Fuzzy logic, galactic swarm optimization, fuzzy systems, adjustment of parameters, fuzzy controller

DOI: 10.3233/JIFS-191873

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3545-3559, 2020

Authors: Lin, Jian | Li, Meiling | Cui, Chunsheng | Tian, Zhiyong

Article Type: Research Article

Abstract: Considering both cardinal characteristics and double powers, the anti-symmetric interval excess value is defined. The least square pre-nucleolus for interval cooperative games is presented by making a single-objective programming model. We obtain the analytic expression of least square pre-nucleolus using Lagrange multiplier method, and construct an effective quadratic programming model to derive the least square pre-nucleolus of incomplete interval cooperative games. In addition, the application of least square pre-nucleolus in land pollution control is provided to show the validity of the proposed solution concepts.

Keywords: Least square pre-nucleolus, interval excess value, cooperative game, incomplete payoff

DOI: 10.3233/JIFS-191882

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3561-3575, 2020

Authors: Van Hop, Nguyen

Article Type: Research Article

Abstract: In this paper, we investigate all relative relationships between two fuzzy numbers. Then, we introduce new relative measures to compare two fuzzy numbers instead of using absolute value to represent the fuzzy number. These measures address the dominant level that one fuzzy number is better than the other in terms of its position and shape. The so-called absolute fuzzy dominant degree and relative fuzzy dominant degree are developed to measure the differences between two fuzzy numbers applying for different types of constraint. These measures could capture all the shape’s characteristics and relative positions of fuzzy numbers. Finally, the fully fuzzy …multi-objective decision making (FFMODM) problem is solved by using these fuzzy dominant degrees. For validation, we compare our approach to the fuzzy ranking method of the linear ranking function. Our obtained results show better performance. Show more

Keywords: Fuzzy dominant degree, linear ranking function, fully fuzzy multi-objective linear programming problem

DOI: 10.3233/JIFS-191888

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3577-3595, 2020

Authors: Wang, Guixiang | Shen, Chenjie | Wang, Yanyan

Article Type: Research Article

Abstract: In this paper, the problem of approximating general fuzzy number by using multi-knots piecewise linear fuzzy number is studied. First, r  - s -knots piecewise linear fuzzy numbers are defined, and the conceptions of the I -nearest r  - s -knots piecewise linear approximation and the II -nearest r  - s -knots piecewise linear approximation are introduced for a general fuzzy number. Then, most importantly, we set up the methods to get the I -nearest r  - s -knots piecewise linear approximation and the II -nearest r  - s -knots piecewise linear approximation for a general fuzzy number. And then, we investigate some properties of …the new approximation operators. Finally, we also present specific examples to show the effectiveness, usability and advantages of the methods proposed in this paper, and compare the methods with some other approximation algorithms. Show more

Keywords: Approximations, membership functions, fuzzy numbers, multi-knots piecewise linear fuzzy numbers

DOI: 10.3233/JIFS-191896

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3597-3615, 2020

Authors: Mishra, Amit Kumar | Joshi, Nisheeth | Mathur, Iti

Article Type: Research Article

Abstract: Analysis of the terrorist network is a process to analyze or deriving Useful information from the available network data. Ranking The Terrorist nodes within a terrorist network in identifying the most influential node is essential for the elaboration of Covert network mining. The purpose of this paper is to implement an approach of two dimensional criteria weight determination along with logarithmic concept implementation for vital node investigation in term of their influential ability. Betweenness, Closeness, Eigenvector, Hub, In-degree, Inverse closeness, Out-degree and Total degree considered as criteria and terrorist involved in 9/11 terrorist attack considered as alternatives used to formulate …a decision problem. Although an integrated approach of Fuzzy based subjective-Aggregation concept based objective criteria weight determination and Ranking alternatives by the implementation of the logarithmic concept is used to solve multi criteria decision problems in order to show the application of most centralized node identification process which can be obtained easily by classification and selection problem solution using multiple criteria and alternatives. Show more

Keywords: Social network, Social Network Analysis(SNA), Terrorist network analysis(TNS), Fuzzy based criteria weight, Aggregation criteria weighting, Approach of logarithmic concept(APLOCO), Multi Criteria Decision Making(MCDN), Centrality measures, Most influential node

DOI: 10.3233/JIFS-191899

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3617-3631, 2020

Authors: Xiao, Wei | Dey, Arindam | Son, Le Hoang

Article Type: Research Article

Abstract: Picture fuzzy graph (PFG) is an extended version of intuitionistic fuzzy graph (IFG) to model the uncertain real world problems, in which IFG may fail to model those problems properly. PFG is more precise, flexible and compatible than IFG to deal the real-life scenarios which consists of information these types: yes, abstain, no and refusal. The main focus of our study is to present the concept of isomorphic PFG, regular PFG (RPFG) and picture fuzzy multigraph. In this paper, we present the notation of RPFG. Many different types of RPFGs such as regular strong PFG, regular complete PFG, complete bipartite …PFG and regular complement PFG are introduced. We also describe the concepts of d n and td n -degree of a vertex in a RPFG. Based on those two types of degrees, we classify the regularity of PFG into 3 type’s namely, d n - RPFG, td n -RPFG and n - highly irregular PFG. Several theorems of those RPFG are presented here. We define the busy vertex and free vertex in a RPFG. We present the notations of μ -complement, homomorphism, isomorphism, weak isomorphism and co weak isomorphism of RPFG. Some significant theorems on isomorphism and μ - complement of RPFG are derived here. We also introduce the notation of picture fuzzy multigraph. We present a mathematical model of communication network and transportation network by using picture fuzzy multigraph and real time data are collected so that the transportation network/communication network can work efficiently. Show more

Keywords: Regular fuzzy graph, picture fuzzy set, intuitionistic fuzzy graph

DOI: 10.3233/JIFS-191913

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3633-3645, 2020

Authors: Xiao, Wenbin | Zhu, Shunying

Article Type: Research Article

Abstract: With the continuous perfection of the technology of automated vehicles (AV), data exchange can be conveniently carried out between different vehicles and infrastructures, which makes it easier to collect different types of traffic parameters. Therefore, under AV environment, the vehicle status can be determined to obtain the periodic arrival rate of movements and a more efficient control strategy can be designed. The combination styles of phase movement (PM), an important factor of the signal control, will also become more complicated for intersection signal control. The current methods about the PM combination styles only considered two kinds of movement combination styles, …and cannot get the extensive phase combination (PC) schemes in AV environment. This paper documents a new PM combination method by fractionalized movement compatibility relations, and uses discrete mathematics to calculate overall PC schemes. Then, a PM dynamic combination control method is proposed to optimize cyclically signal control. The analysis results of numerical tests showed that the average vehicle of the proposed method is reduced by 6.9 % and 14.5 % for 20 signal cycles, respectively, and the total throughput can be increased by 4.3% and 7.8%, respectively, compared with the dynamic timing control mode and the fixed control mode. Results show that the proposed method could significantly improve intersection control effectiveness. Show more

Keywords: Intersection control, movements compatible, phase combination schemes, phase movement dynamic combination, vehicle delay

DOI: 10.3233/JIFS-191939

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3647-3664, 2020

Authors: Wang, Jing | Yan, Bing | Wang, Guohao | Yu, Liying

Article Type: Research Article

Abstract: Quality function deployment (QFD) is an useful tool to solve Multi-criteria decision making, which can translate customer requirements (CRs) into the technical attributes (TAs) of a product and helps maintain a correct focus on true requirements and minimizes misinterpreting customer needs. In applying quality function deployment, rating technical attributes from input variables is a crucial step in fuzzy environments. In this paper, a new approach is developed, which rates technical attributes by objective penalty function and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) based on weighted Hamming distance under the case of uncertain preference characteristics …of decision makers in fuzzy quality function deployment. A pair of nonlinear programming models with constraints and a relevant pair of nonlinear programming models with unconstraints called objective penalty function models are proposed to gain the fuzzy important numbers of technical attributes. Then, this paper compares the fuzzy numbers by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method based on weighted Hamming distance in consideration of the uncertain preference characteristics of decision makers. To end with, the developed method is examined with the numerical examples. Show more

Keywords: Quality function deployment, objective penalty function, fuzzy TOPSIS, weighted Hamming distance

DOI: 10.3233/JIFS-191955

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3665-3679, 2020