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