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

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