Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

Authors: Yan, Shuli | Liu, Sifeng | Zeng, Xiangyan

Article Type: Research Article

Abstract: A new dynamic multi-attribute group decision making method based on matrix grey target decision model is proposed. The attributes’ data of alternatives about decision makers in different stages are represented by matrices, and they are considered as performance values in 4-dimensional space. The best, worst attributes’ values in other 3-dimensions formed the new matrices, which are defined as expected bull’s-eye, unexpected bull’s-eye, and then the deviations of alternatives and expected, unexpected bull’s eye are presented using matrix norm. The alternatives are ranked by the deviations. Finally, the examples are provided to illustrate the proposed method.

Keywords: Dynamic multi-attribute group decision making, Matrix grey target model, 4-dimensional space, matrix norm

DOI: 10.3233/JIFS-181973

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1043-1053, 2019

Authors: Zhou, Linna | Shen, Leping | Yang, Chunyu

Article Type: Research Article

Abstract:  This paper presents a disturbance-observer based sliding mode control (SMC) for fuzzy singularly perturbed systems (SPSs) with uncertainties and disturbances. Firstly, we designed a linear sliding surface. The sliding surface parameter matrix is determined by solving linear matrix inequalities (LMIs). The stability of the sliding mode is proved by a Lyapunov function. Secondly, a disturbance observer is designed to estimate the disturbance, and the obtained disturbance estimate is incorporated in the design of SMC. The reachability condition under the fuzzy SMC law is shown to be satisfied. Finally, simulation results show the feasibility and effectiveness of the proposed control method.

Keywords: Singularly perturbed systems (SPSs), sliding mode control (SMC), linear matrix inequality (LMI), T-S fuzzy model

DOI: 10.3233/JIFS-181995

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1055-1064, 2019

Authors: Thao, Nguyen Xuan | Smarandache, Florentin

Article Type: Research Article

Abstract: Pythagorean fuzzy sets are an extension of the intuitionistic fuzzy sets, and it also overcomes the limitations of the intuitionistic fuzzy sets. The entropy of a Pythagorean fuzzy set (PFS) is a measure of uncertainty related to the PFS. In this article, we exploit the concept of probability for defining the fuzzy entropy of Pythagorean fuzzy sets as an extension of the fuzzy entropy of Intuitionistic fuzzy sets (IFSs). Compared to some previous measures, the new measure is simpler, closer to the statistical significance and it reflects better fuzzy properties. After that, we give some numerical examples to compare our …proposed entropy measure to some existing entropy of Pythagorean fuzzy sets. The results on numerical examples show that the proposed entropy measures seem to be more reliable for presenting the degree of fuzziness of a PFS and/or IFS. We also proposed a COPRAS multi-criteria decision-making method with weights calculated based on the proposed new entropy measure. The illustrated numerical example shows that the calculated results according to the proposed new method are similar to the calculation results according to some other existing methods. Show more

Keywords: Pythagorean fuzzy sets, entropy measures, COPRAS method

DOI: 10.3233/JIFS-182540

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1065-1074, 2019

Authors: Yong, Rui | Zhu, Aqin | Ye, Jun

Article Type: Research Article

Abstract:  A cubic hesitant fuzzy set is a hybrid set which can express uncertain and hesitancy fuzzy information simultaneously. For multiple attribute decision-making problems in engineering practice, the complicated decision information is generally incomplete and indeterminate. Cubic hesitant fuzzy set can be a valuable tool for describing uncertain and hesitancy fuzzy information in uncertain decision environment. Nevertheless, no similarity measure has been used to solve decision-making problems under cubic hesitant environment in previous studies. This paper presents a Jaccard similarity measure between cubic hesitant fuzzy sets and investigates their properties. Then a multiple attribute decision-making method is developed based on the …weighted Jaccard similarity measure under cubic hesitant environment. Using this method, the similarity measure values between the ideal alternative and each evaluated alternative are determined to obtain the ranking order of similarity measure values and the best alternative. An illustrative example of the selection problem of project alternatives is utilized to illustrate the application of the developed decision-making method. Finally, the validity of the proposed decision-making method was demonstrated based on the comparison of the decision-making results of the illustrative example with two distance-based similarity measures. Show more

Keywords: Cubic hesitant fuzzy set, multiple attribute decision-making, similarity measure, Jaccard measure

DOI: 10.3233/JIFS-182555

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1075-1083, 2019

Authors: Ulaganathan, M.S. | Devaraj, D.

Article Type: Research Article

Abstract: The Maximum Power Point Tracking (MPPT) controller plays a vital role in maximizing power output from the solar Photovoltaic (PV) sources. The tracking efficiency of the MPPT controller is affected by a rapidly varying environmental condition. This paper presents a novel MPPT controller for standalone PV system based on a Neural Network (NN) and Gain-scheduled Proportional Integral (GS-PI) controller to track the fast-changing Maximum Power Point (MPP).The NN model is trained to predict the operating parameters of the PV array at which maximum power is generated. The gain scheduled PI controller parameters are optimally tuned with Real-coded Genetic Algorithm (RGA) …to improve the controller performance. The developed MPPT controller is used to control the power converter in the solar PV system. The PV array along with the control scheme is developed using LabVIEW and Multisim environment. Further, the performance of the developed control strategy is experimentally validated with solar PV emulator and DC-DC boost converter under the varying irradiation conditions. The tracking performance of the developed MPPT controller is compared with the modified Perturb and Observe and NN+PI controller based MPPT controller. The experimental results reveal that the tracking performance of the developed MPPT technique is much improved and more accurate in MPP tracking. Show more

Keywords: Neural networks, Real Coded Genetic Algorithm, gain scheduled PI controller, P&O algorithm

DOI: 10.3233/JIFS-182556

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1085-1098, 2019

Authors: Zeng, Wenyi | Li, Deqing | Yin, Qian

Article Type: Research Article

Abstract: Hesitant fuzzy linguistic term set(HFLTS), which permits decision makers to use several linguistic terms to assess a variable, is a useful tool to deal with situations in which people are hesitant in providing their assessment. In this paper, we introduce the concept of weighted hesitant fuzzy linguistic term set(WHFLTS), in which different weights are designed to these possible linguistic terms, and the weights indicate that the decision maker has different confidence in giving every possible assessment. After that, we introduce some operations such as union, intersection, complement, multiplication of weighted hesitant fuzzy linguistic elements, discuss their operation properties, and …propose the score function of the weighted hesitant fuzzy linguistic element(WHFLE) to compare weighted hesitant fuzzy linguistic elements(WHFLEs). Furthermore, we introduce the concept of hesitance degree of weighted hesitant fuzzy linguistic element, present four aggregation operators such as the weighted hesitant fuzzy linguistic weighted averaging(WHFLWA) operator, the weighted hesitant fuzzy linguistic weighted geometric(WHFLWG) operator, the generalized weighted hesitant fuzzy linguistic weighted averaging(GWHFLWA) operator and the generalized weighted hesitant fuzzy linguistic weighted geometric(GWHFLWG) operator to aggregate weighted hesitant fuzzy linguistic information, and build the mathematical model of multi-criteria group decision making based on weighted hesitant fuzzy linguistic environment. Finally, two numerical examples are used to illustrate the effectiveness and applicability of our proposed method. Show more

Keywords: Hesitant fuzzy sets, Hesitant fuzzy linguistic term sets, Weighted hesitant fuzzy linguistic term sets, Aggregation operator, Group decision making

DOI: 10.3233/JIFS-182558

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1099-1112, 2019

Authors: Yi, Zeren | Li, Guojin | Chen, Shuang | Xie, Wei | Xu, Bugong

Article Type: Research Article

Abstract:  This paper presents a navigation algorithm based on interval type-2 fuzzy neural network fitting Q-learning (IT2FNN-Q), and succeeds in providing a solution for mobile robot navigation in complex environments. The algorithm utilizes the fuzzy reasoning adaptive ability and extensive functional approximation features of IT2FNN to solve this problem, mapped from state space to action space, of the Q-learning algorithm in unknown environments. Compared with the BP fitting Q-learning algorithm (BP-Q), IT2FNN-Q endows the robot with better adaptive and real-time decision-making abilities and solves the slow convergence and nonconvergence problems, through its local approximation. By comparison with the fuzzy neural network …fitting Q-learning algorithm (FNN-Q), this proposed algorithm has more advantages for dealing with the external uncertainty, enabling the robot to complete a better path with less fuzzy rules. The results of the simulation and comparison of the proposed method with FNN-Q and BP-Q revealed that the mobile robot can navigate itself in complex environments with fewer steps, obtaining more reward values by adopting the algorithm presented in this paper. Show more

Keywords: Mobile robots, Q-learning, robot navigation, interval type-2 fuzzy neural network (IT2FNN)

DOI: 10.3233/JIFS-182560

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1113-1121, 2019

Authors: Xing, Yuping | Zhang, Runtong | Zhu, Xiaomin | Bai, Kaiyuan

Article Type: Research Article

Abstract: Multiple attribute decision making (MADM) problems widely exist in real decision making, and MADM methods with linguistic information have achieved great success. However, as the complexity of decision making problems is increasing in the real world, it is of great necessity to further develop new expression of evaluation information and aggregation technologies that can reflect the correlation among multi-attributes under uncertain decision-making environment. In response, this paper originally presents q -rung orthopair fuzzy uncertain linguistic set (q -ROULS) by combining q -rung orthopair fuzzy set (q -ROFS) and uncertain linguistic set (ULS). Then operational laws, expected functions and accuracy functions …of q -rung orthopair uncertain linguistic variables (q -ROULVs) are also defined. Considering the correlation between q -ROULVs, we propose a family of q -rung orthopair fuzzy uncertain linguistic Choquet integral operators to aggregate q -rung orthopair uncertain linguistic information. Further, a novel MADM technique is presented based on the proposed q -rung orthopair fuzzy uncertain linguistic Choquet integral operators. The developed MADM method with q -rung orthopair fuzzy uncertain linguistic information enriches fuzzy decision-making theory and provides a new way for decision makers (DMs) under q -rung orthopair fuzzy uncertain linguistic environment. Show more

Keywords: q-rung orthopair fuzzy uncertain linguistic set, q-rung orthopair uncertain linguistic choquet integral operators, multi-attribute decision making

DOI: 10.3233/JIFS-182581

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1123-1139, 2019

Authors: Renisha, G. | Jayasree, T.

Article Type: Research Article

Abstract: The rapid development in technology has led to a colossal surge in the use of biometric authentication system. Speaker identification biometric is one of the fields that is under progress and demands more and more precision. The objective of this research is to explore the issue of identifying a speaker from voice regardless of the content. Perceptual Wavelet Packet Transform (PWPT) and Artificial Neural Networks (ANN) approach are discussed in this paper for speaker identification. Perceptual Wavelet Packet Cepstral Coefficients (PWPCC) are used for transforming speech into spectral feature vectors, and the most germane aspects of the speech signal are …selected from the energy and variance distribution characteristics. These selected attributes are presented to the Cascaded Feedforward Neural Network (CFNN) and trained with Levenberg-Marquardt Back Propagation (LMBP) algorithm for further classification. The performance of the network is determined by evaluating the Speaker Identification Rate (SIR). For comparison, five different gradient descent training algorithms are considered and it is found that the LMBP produces better performance. The proposed model is evaluated for clean as well as noisy speech at various SNR levels and is found to be competitive, and the experimental results show significant improvement in speaker identification rate compared with other classical methods. Show more

Keywords: Perception, wavelet, speaker, speech, neural network

DOI: 10.3233/JIFS-182599

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1141-1153, 2019

Authors: Maini, Tarun | Kumar, Abhishek | Misra, Rakesh Kumar | Singh, Devender

Article Type: Research Article

Abstract:  This paper focuses on Fuzzy rough set, which is the fusion of fuzzy sets and rough sets theory for doing feature selection. For selecting the appropriate feature subset, swarm algorithms are used. The fitness function used here is Fuzzy Rough Dependency Measure. This paper demonstrates that by optimizing the fitness function, swarm algorithms are capable to select the best subset of features. Further, in this paper, an attempt has been made to improve the capability of the swarm based algorithms such as Intelligent Dynamic Swarm (IDS) and Particle Swarm Optimization (PSO) through modified initialization of solutions, for picking the appropriate …features for the feature selection task. Improvement in the size of reducts and classification accuracy of these reducts are observed when initialization is done using the proposed method. Statistical t-tests have also been performed for the validation of the results. Show more

Keywords: Feature selection, fuzzy rough set, rough set, particle swarm optimization, intelligent dynamic swarm, classification accuracy, t-test

DOI: 10.3233/JIFS-182606

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1155-1164, 2019

Authors: Afrasiabi, Mousa | Afrasiabi, Shahabodin | Parang, Benyamin | Mohammadi, Mohammad

Article Type: Research Article

Abstract: Differential protection of power transformers, as the fundamental protection, plays an important role in power system reliability and security. The main challenge in differential protection is discrimination between internal faults of power transformers and inrush current. Development of differential protection, especially discrimination between internal faults from other disturbances, have been a favorite subject in power system protection field over decades. Traditional methods proposed so far have several shortcomings: i) high computational burden, ii) sensitivity to noise, iii) being influenced by predefined threshold value/additional parameters/different models at varying ambient conditions, and iv) dependence on handcrafted or spectral analysis to extract features. …Deep neural networks (DNN) is selected as the potential solution in this paper, which is able to capture the hierarchical features of a half-cycle of raw data. This paper proposes convolutional neural networks (CNN), in which batch normalization and scaled exponential linear unit (SELU) are merged to enhance differential protection performance. In order to generalize the CNN-based differential protection, several external factors, i.e. the compensation error of current transformer (CT) saturation, series compensated line, and superconducting fault current limiter (SFCL) are conducted to verify the reliability of the proposed method through different reliability metrics. The simulation and experimental results are assessed to show high reliability and the speed of the proposed method. Show more

Keywords: Inrush current, Power transformer protection, Differential protection, Convolutional neural network (CNN)

DOI: 10.3233/JIFS-182615

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1165-1179, 2019

Authors: Hamidi, Mohammad | Borumand Saeid, Arsham | Smarandache, Florentin

Article Type: Research Article

Abstract: This study introduces the notion of n -valued refined neutrosophic (EQ -subalgebras)EQ –(pre)filters and investigates some of their properties. We show how to construct n -valued refined neutrosophic EQ -(pre)filters and determine the relationship between n -valued refined neutrosophic EQ -(pre)filters and EQ –(pre)filters with respect to (α , β , γ )-level set. Finally, the extension of n –valued refined neutrosophic EQ –(pre)filters are considered via homomorphisms and some applications of n –valued refined neutrosophic EQ –(pre)filters are presented.

Keywords: n–valued refined neutrosophic EQ–subalgebras, n–valued refined neutrosophic EQ–(pre)filters

DOI: 10.3233/JIFS-182618

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1181-1196, 2019

Authors: Kutlu Gündoğdu, Fatma | Kahraman, Cengiz

Article Type: Research Article

Abstract: The extensions of ordinary fuzzy sets such as intuitionistic fuzzy sets (IFS), Pythagorean fuzzy sets (PFS), and neutrosophic sets (NS), whose membership functions are based on three dimensions, aim at collecting experts’ judgments more informatively and explicitly. In the literature, generalized three-dimensional spherical fuzzy sets have been developed by Kutlu Gündoğdu and Kahraman (2019), including their arithmetic operations, aggregation operators, and defuzzification operations. Spherical Fuzzy Sets (SFS) are a new extension of Intuitionistic, Pythagorean and Neutrosophic Fuzzy sets, a SFS is characterized by a membership degree, a nonmembership degree, and a hesitancy degree satisfying the condition that their squared sum …is equal to or less than one. These sets provide a larger preference domain in 3D space for decision makers (DMs). In this paper, our aim is to extend classical VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to spherical fuzzy VIKOR (SF-VIKOR) method and to show its applicability and validity through an illustrative example and to present a comparative analysis between spherical fuzzy TOPSIS (SF-TOPSIS) and SF-VIKOR. We handle a warehouse location selection problem with four alternatives and four criteria in order to demonstrate the performance of the proposed SF-VIKOR method. Show more

Keywords: Spherical fuzzy sets, multicriteria decision making, VIKOR, warehouse location selection

DOI: 10.3233/JIFS-182651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1197-1211, 2019

Authors: Zhu, Cheng | Mesiar, Radko | Yager, Ronald R. | Merigo, Jose | Qin, Jindong | Feng, Xiangqian | Jin, Lesheng

Article Type: Research Article

Abstract: In this work, we propose some two-layer preference models that can be appropriately applied in management problems such as the group decision making about predicting the future market share of certain product. By introducing the convex IOWA operator paradigm and some related properties and definitions, we list some detailed preference and inducing preference models to demonstrate and exemplify the proposed conceptual frame of two-layer preference model. The convex IOWA operator paradigm facilitates the modeling process and, from mathematical view, makes it stricter. When relevant inducing information and aggregation selection change, the proposed models can be easily adapted to accommodate more …different applications in decision making and evaluation. Show more

Keywords: Aggregation operators, decision making, induced aggregation, ordered weighted averaging operators, orness/andness, preference model

DOI: 10.3233/JIFS-182671

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1213-1221, 2019

Authors: Li, Jiansheng | Gong, Zengtai | Shao, Yabin

Article Type: Research Article

Abstract: Intuitionistic fuzzy transform is an approximate method based on the intuitionistic fuzzy partition. To begin with, a novel definition of intuitionistic fuzzy partition is given, and the properties of triangular intuitionistic fuzzy partition are also given. Secondly, the method of intuitionistic fuzzy transform is introduced, which transforms a continuous function into two gravity vectors according to the membership and non-membership functions that based on intuitionistic fuzzy partition. Some fundamental properties of intuitionistic fuzzy partition are surveyed. Thirdly, the method of inverse intuitionistic fuzzy transform is established by using the previous gravity vectors corresponding to the intuitionistic fuzzy partition. The results …show that the approximate function of the original one can be rebuilt by the membership and non-membership functions respectively. even a hybrid approximate function can be rebuilt by both the membership and non-membership functions. Finally, some elementary properties of the inverse intuitionistic fuzzy transform are studied and the method is illustrated by a specific example. Show more

Keywords: Intuitionistic fuzzy set, intuitionistic fuzzy partition, intuitionistic fuzzy transform, inverse intuitionistic fuzzy transform

DOI: 10.3233/JIFS-182681

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1223-1232, 2019

Authors: ElAraby, M.E. | Abuelenin, Sherihan M. | Moftah, Hossam M. | Rashad, M.Z.

Article Type: Research Article

Abstract: Cloud computing offers elastic features to alleviate the challenges of web crawling. Building crawlers in a scalable fashion has become highly needed. This paper proposes a new Focused Crawler (FC) architecture that can be introduced as a service over the cloud computing. The proposed FC has a service called a Topic Filter Service (TFS), which is responsible for filtering retrieved pages before indexing and extracting links to add them in the crawling queue. TFS relies on the Deep Neural Network (DNN) classifier. TFS is trained by a dataset. This dataset is processed by an outlier rejection using support vector machine …classifier. Moreover, this proposed FC has a further service called Concept Weight Handler (CWH). It is responsible for handling the keywords such as concepts based on meanings and it calculates the weight of each concept. Experimental results show that cloud computing services provide a better environment for running and improving the speed of crawling. The proposed classifier has been tested in comparison with other classification techniques and has proved highly accurate. The overall accuracy offered by the employed architecture confirms that the effectiveness and performance of the proposed FC is high. Show more

Keywords: Focused Crawler, deep neural network, cloud computing, topic filter service, concept web page

DOI: 10.3233/JIFS-182683

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1233-1245, 2019

Authors: Yang, Rong | Wang, Yun | Hui, Bin | Qiu, Li

Article Type: Research Article

Abstract: The Choquet integral, established with respect to signed fuzzy measure, is an effective aggregation tool in information fusion and classification. Critical coefficients in Classifiers based on Choquet Integral (CCI) are the values of signed fuzzy measure. Currently, determination of these coefficients is either preset subjectively by experience, or retrieved by global optimization methods which are time-consuming, especially when the number of predictive attributes is large. In this paper, an analytic derivation to retrieve the values of signed fuzzy measure in CCI is proposed via discriminant analysis for the first time. On this basis, a generalized Hierarchical Classifiers based on Choquet …Integral (HCCI) is established, where a set of scaling parameters is added to CCI to balance the scales of different dimensions. Retrieving of the scaling parameters and the signed fuzzy measure is achieved by a hierarchical structure of program in which a genetic algorithm is embedded with the analytic derivation being proposed in this paper. Performance validation on synthetic and benchmark data sets are conducted to reveal the feasibility and effectiveness of the proposed methods. Show more

Keywords: Classification, Choquet integral, fuzzy measure, discriminant analysis, genetic algorithm

DOI: 10.3233/JIFS-182699

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1247-1258, 2019

Authors: Abdullah, Lazim | Mohd, Wan Rosanisah Wan

Article Type: Research Article

Abstract: Pythagorean fuzzy Hamacher aggregation operator is one of the aggregation operators in a Pythagorean fuzzy decision making environment. In most cases, it is assumed that all elements in Pythagorean fuzzy set (PFSs) are independent. However, in real life of decision problems, most of the criteria are interrelated. Population size in a solid waste management decision, for example, is related to human health since the two criteria are mutually dependent. This paper aims to introduce an aggregation operator that purposely dealt with the interactions between elements of PFSs. The Choquet integral operator is used to propose an innovation to the Pythagorean …fuzzy Hamacher operator. Pythagorean fuzzy Hamacher Choquet integral average operators (PFHCIA) and Pythagorean fuzzy Hamacher Choquet integral geometric operators (PFHCIG) are proposed. The beauty of the proposed operators is it consider the interaction of the criteria in the decision making process. The proposed aggregation operators are the extension to the Pythagorean fuzzy Hamacher aggregation operators where Choquet integral is used to handle interactions between criteria. As the case study is considered, a water resource management problem is presented to portraythe application the proposed approach. Comparable results are also presented to check its feasibility and effectiveness. It is shown that the ranking using the proposed operators are inconsistent with the existing method. The importance of an aggregation function that can capture the problem of interdependence between the criteria is the main contribution of this paper. Show more

Keywords: Pythagorean fuzzy set, aggregation operators, hamacher operation, decision-making, choquet integral

DOI: 10.3233/JIFS-182704

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1259-1274, 2019

Authors: Mehmood, Faisar | Ali, Rashid | Hussain, Nawab

Article Type: Research Article

Abstract:  In this paper, by introducing the concept of a fuzzy rectangular-b -metric space, the notion of a fuzzy metric space and a fuzzy b -metric space are generalized. The well known metric fixed point theorems are established in the setting of fuzzy rectangular b -metric spaces and illustrated by examples. To show the significance of our result an application is presented to establish the existence of a solution of integral equation. Our results generalize many existing theorems in the literature.

Keywords: b-metric space, Fuzzy b-metric space, Fixed points, Contractions

DOI: 10.3233/JIFS-182719

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1275-1285, 2019

Authors: Manuel Escaño, Juan | Sánchez, Adolfo J. | Witheephanich, Kritchai | Roshany-Yamchi, Samira | Bordons, Carlos

Article Type: Research Article

Abstract: In this work, a novel methodology is presented to reduce the computational complexity of applying explicit solution of Model Predictive Control (MPC). The methodology is based on applying the functional principal component analysis , providing a mathematically elegant approach to reduce the complexity of rule-based systems, like piecewise affine systems, allowing the reduction of the number of consequents and combining and merging the antecedents. Thus, the application of MPC is allowed in systems with low computational requirements, such as programmable logic controllers, embedded systems, etc. The proposed design has been validated using an industrial distiller model.

Keywords: Piece wise affine, functional principal component analysis, model predictive control, fuzzy control

DOI: 10.3233/JIFS-182743

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1287-1298, 2019

Authors: Su, Hongsheng | Wang, Danting | Su, Lan

Article Type: Research Article

Abstract: In view of defects that traditional Fuzzy Analytical Hierarchy Process (FAHP) cannot accurately describe the ambiguity and randomness of the assessment, and as well as inconsistency existed in judgment process, in this paper a novel risk evaluation method is proposed using Fuzzy Failure Modes Effects and Criticality Analysis (FMECA) based on could model. The method firstly applies FMECA to identify the risk, and then uses FAHP to determine the subjection degree function with cloud model based. In the end, the group decision can be conducted with the synthetically aggregated cloud model, which can be directly observed through the distribution of …the cloud pictures. Compared with traditional FAHP, the relevant practical examples in Chinese train control (CTC) systems show that the results of the two possess difference due to their original data coming from different 20-expert questionnaires, the reason is found that there exists inconsistence in 20-expert questionnaires on FAHP via t -examination method. Hence, though another 20-expert questionnaires and after inconsistence test, we obtain consistent result in both methods, but the Fuzzy-FMECA with cloud model based could implement the transformation between exact value and quantized one by incorporating the ambiguity and randomness, and provide more abundant information than subjection degree function of the conventional FAHP method, and possesses better consistency, and is a feasible and more effective decision method. In addition, the correlation coefficient method and center-of-gravity method are also applied to verify the correctness and effectiveness of the proposed method, and such that it can be widely applied to solve real-world practical issues. Show more

Keywords: Risk, fuzzy analytical hierarchy process (FAHP), cloud model, Chinese train control(CTC) systems, t-examination, validation

DOI: 10.3233/JIFS-182745

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1299-1309, 2019

Authors: Jia, Ruru | Bai, Xuejie | Song, Fengxuan | Liu, Yankui

Article Type: Research Article

Abstract: Sustainable development problem involves several conflicting criteria on economy, energy, environment and social aspects and some sources of uncertainty due to its attribute. It is necessary to mitigate risks in sustainable development schedule. However, the existing literature includes limited quantitative research on robust strategies for sustainable development under uncertainty. Under these concerns, this paper presents a robust multi-objective optimization formulation for allocating labor across economic sectors to simultaneously satisfy economy (gross domestic product, GDP), environment (greenhouse gas (GHG) emissions), energy (electricity) and society (labor), in which the per capita GDP, per capita electricity consumption, per capita GHG and per capita …rate of unemployment are robust uncertainty. There are three conflicting objectives in our sustainable development problem. The first objective maximizes the sectoral GDP, the second objective minimizes the sectoral electricity consumption and the third objective minimizes the sectoral GHG emissions. We adapt ɛ -constraint method to deal with the multiple objectives for the sustainable development problem, and obtain a more flexible result via an interactive decision-making process. Since uncertainty has often led to computationally intractable models, we reformulate the proposed model using robust optimization method into the tractable robust counterpart (RC) forms under two types of uncertainty sets. Finally, to demonstrate the effectiveness and applicability for our model, we conduct a case study for meeting year 2030 sustainable development of the United Arab Emirates (UAE). The numerical results show: (a) the robust multi-objective model is effective in uncertain environment and provides a reliable decision tool than deterministic model for integrated multi-objective sustainable development problem; (b) when the possibility distributions of uncertain parameters are available, fuzzy optimization model can provide better decision-making than robust model under box uncertainty set. Show more

Keywords: Sustainable development, multiple objectives, robust optimization, fuzzy optimization

DOI: 10.3233/JIFS-182763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1311-1326, 2019

Authors: Peng, Xindong

Article Type: Research Article

Abstract:  This paper is designed to show deeper standpoints for dealing the decision making issues based on intuitionistic fuzzy soft set (IFSS). Firstly, we propose a novel definition and formula of similarity measure on intuitionistic fuzzy information, which can reserve more original judgment information. Afterwards, we present a combination weight that take the objective weight (obtained by grey system theory) and the subjective weight into consideration. Later, three intuitionistic fuzzy soft methods based on similarity measure, MABAC and EDAS are presented for dealing the decision making issues. Finally, the validity of methods are stated by some practical examples. The key characteristics …of the developed methods have no strict requirements for decision data and possess a stronger ability in differentiating the best alternative. Show more

Keywords: Similarity measure, combination weights, IFSS, MABAC, EDAS

DOI: 10.3233/JIFS-182768

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1327-1341, 2019

Authors: Dinçer, Hasan | Yüksel, Serhat

Article Type: Research Article

Abstract: The selection of investment strategies is one of prominent issues for the service industries in the competitive market environment. The aim of the study is to evaluate the investment strategies for the European tourism industry using a hybrid decision making approach based on the interval type-2 fuzzy sets. For this purpose, a set of criteria and dimensions for the investments strategies of the European tourism is proposed. Interval type-2 fuzzy DEMATEL is applied to weight the criteria and dimensions and interval type-2 fuzzy MOORA is used for selecting the best investment strategies for the European tourism industry. The novelty of …the study is to propose a set of investment strategies for the European tourism and the extended methods for DEMATEL and MOORA under the fuzzy environment. A novel hybrid approach is also proposed to the decision-making process based on the interval type-2 fuzzy sets. The major results are summarized as European countries should firstly focus on increasing the number of touristic facilities in the coast line to attract the attention of the tourists. Similarly, it can also be beneficial for these countries make more private security investment for the tourists to feel more secured while visiting historical places. Owing to these strategies, it can be possible to develop European tourism industry. Show more

Keywords: Tourism, investment strategies, interval type-2 fuzzy DEMATEL, interval type-2 fuzzy MOORA, industry

DOI: 10.3233/JIFS-182773

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1343-1356, 2019

Authors: Bouaita, Bilal | Moussaoui, Abdelouahab | Bachari, Nour El Islam

Article Type: Research Article

Abstract: The Meteosat Second Generation (MSG) satellite can be used to estimate rainfall through the multispectral images, which are provided every 15 min across 12 channels. However, most studies have not maximized the terabytes of data provided by the channels in this satellite, which are potentially rich in new resources that need to be exploited. Moreover, these studies classify pixels conventionally, where a pixel is considered either 100% precipitant or 0% (no-precipitant), whereas actually it cannot be classified in a clear and unambiguous way. To address this problem, we propose a method that exploits the images of the channels and constructs …an estimation model in the form of fuzzy association rules to estimate the rainfall in Northeastern Algeria. Each rule is in if (condition)-then (conclusion) form, where the condition is a combination of the various fuzzy classes of MSG images, and the conclusion contains a single fuzzy class that represents the intensities of rain: no-rain, low, moderate, and high. The obtained results are compared with the data obtained by the European Organization for the Exploitation of Meteorological Satellites Multisensor Precipitation Estimate program. Show more

Keywords: Data mining, MSG images, apriori algorithm, fuzzy association rules, fuzzy c-means algorithm

DOI: 10.3233/JIFS-182786

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1357-1369, 2019

Authors: Xu, Lan | Li, Peng

Article Type: Research Article

Abstract: Recently, the reform practice of government procurement of public service (GPPS) in China has been promoted gradually and got great breakthrough. Meanwhile, in order to guarantee that the expected goal of this reform achieved, mature and effective regulation is of vital importance. Considering the practical demand, the capability maturity model is applied into the evaluation of quality regulatory capability in GPPS. The concept of quality regulatory capability maturity is proposed, and the evaluation model based on TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method for probabilistic linguistic term sets (PLTSs) is provided. Taking Jiangsu Province …as an example, an empirical study of its quality regulatory capability evaluation for GPPS is conducted, through which, not only comparative results of maturity levels of different cities in Jiangsu is obtained, but the improving measures are also determined. The proposed maturity evaluation model fully reflects experts’ preferences and evaluation information, and is able to point out the direction for regulatory capability’s future promotion level by level, as well as its continual improvement. Show more

Keywords: Government procurement of public service, quality supervision, capability maturity, evaluation, probabilistic linguistic term set

DOI: 10.3233/JIFS-182788

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1371-1384, 2019

Authors: Sağiroğlu, Yasemin | Gözütok, Uğur

Article Type: Research Article

Abstract:  Metric properties, i.e. properties which are invariant relative to the group E  (3) of all Euclidean motions of the 3-dimensional Euclidean space of fuzzy curves are investigated in this paper. E  (3)-equivalence of fuzzy curves is introduced. E  (3)-equivalence of fuzzy curves is given in terms of fuzzy curvature and fuzzy torsion. All correlations between these fuzzy invariants of a fuzzy curve are described.

Keywords: Fuzzy path, fuzzy curve, invariant

DOI: 10.3233/JIFS-182805

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1385-1397, 2019

Authors: Yue, Xiaofeng | Zhang, Hongbo

Article Type: Research Article

Abstract: As one of the most popular image segmentation techniques, multi-level thresholding is widely used. Much work has been done to improve the efficiency of multi-level thresholding, but satisfied affect is hard to achieve. In this paper, a multi-level image segmentation method using between-class variance (Otsu) based on improved bat algorithm (DWBA) with dynamically adjusting inertia weight and velocity stratification theory is proposed. DWBA algorithm has strong global search ability at the beginning. Then, the local search capability is enhanced with numbers increasing of iterations. More importantly, the performance of DWBA further improved, because bats with different fitness values have diverse …velocities. Furthermore, an improved local search strategy is proposed to avoid the current best solution being replaced during iterations. The experimental results established that the proposed DWBA algorithm obtains better outcome than other algorithms. Show more

Keywords: Multi-level image segmentation, DWBA algorithm, dynamically adjusting inertia weight, velocity stratification theory, Otsu

DOI: 10.3233/JIFS-182806

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1399-1413, 2019

Authors: Zhang, Zi-Xuan | Hao, Wen-Ning | Yu, Xiao-Han | Chen, Jun-Yue | Xu, You-Wei

Article Type: Research Article

Abstract:  Due to the fact that individual knowledge is often inadequate and deficient in group decision-making problems, it is commonly seen that the preference information provided by the decision makers are incomplete. To encounter this problem lots of relevant researches have already been carried out. However, previous methods often only take into account either the information of the expert who provided incomplete preference, or information provided by the rest of the group. To be more thorough and comprehensive, this paper combined both parts of the information, by first setting the unknown preference values as output and known ones as inputs, training …the Bayesian regression model with the complete observations of other experts to detect the associations between them, and then putting in the incomplete preference information to predict the unknown ones. Moreover, inspired by the empirical rule of the Gaussian distribution, this paper also propose to combine the concept of confidence interval with that of interval-valued preference relations, by expressing the prediction results with interval-valued fuzzy reciprocal relations to allow some degree of uncertainty. On the basis of that an iterative consensus reaching process incorporated with feedback mechanism is also proposed. Finally a case study of possible application of our proposed model in project performance evaluations is carried out, the results of which then further verify the practicality and validity of our model. Show more

Keywords: Group decision making, incomplete fuzzy reciprocal preference relation, Bayesian linear regression, consensus reaching process

DOI: 10.3233/JIFS-182817

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1415-1434, 2019

Authors: Safaeian, Mojgan | Fathollahi-Fard, Amir Mohammad | Tian, Guangdong | Li, Zhiwu | Ke, Hua

Article Type: Research Article

Abstract: It is generally believed that the process of supplier selection plays a critical role in the purchasing management. To improve the performance of a supply chain network, it is essential to build a strategic and a strong relationships. As such, all firms should select the best suppliers by applying appropriate methods through different selection criteria. An appropriate supplier reduces all purchasing costs as well as increases customer satisfaction to improve the final product and strengthen corporate competitiveness. Due to the natural uncertainty of this dilemma, most of recent works show a great deal of interest in applying uncertainty approaches. The …main innovation of this paper is to develop a new multi-objective model for both supplier selection and order allocation operations considering incremental discount in a fuzzy environment. The proposed model considers the material cost with incremental discount and the transportation cost, holding costs along with its control and interest as well as the possibility of payment, brought back, and replacement costs, simultaneously, for the first time in this research area. Based on the proposed fuzzy model, the Zimmermann fuzzy approach is used in order to covert the model in a single objective form. Accordingly, a Genetic Algorithm (GA) is applied to solve the proposed problem. Based on the multi-objective optimization proposed, a Non-dominated Sorting GA (NSGA-II) is also employed to solve the developed model through the multi-objective assessment methodologies. Finally, a comprehensive evaluation and discussion based on the results are provided to reveal the performance of developed methodology. Show more

Keywords: Supplier selection, order allocation, incremental discount, zimmermann fuzzy approach, genetic algorithm, NSGA-II

DOI: 10.3233/JIFS-182843

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1435-1455, 2019

Authors: Xun, Xin | Xin, Xiao Long

Article Type: Research Article

Abstract: In this paper, we introduce the notions of node, nodal filter and seminode in equality algebras and study some properties of them. First, we study the relation between nodes and other specific elements. Furthermore, by defining some operations on N F ( E ) , which is the set of all nodal filters in an equality algebra E , we prove that ( N F ( E ) , ∧ , ↔ , E ) is an equality algebra. In fact, we show that N F ( E ) …is a Hertz algebra, BCK-algebra, Hilbert algebra, Kleene algebra and semi-De Morgan algebra. Then we investigate the relation among nodal filters and (positive) implicative, fantastic, prime, and boolean filters in any equality algebras. Finally, we study the relation between nodes and seminodes. And we prove the set of all seminodes SN (E ) is a lattice, Heyting algebra and Hertz algebra under the conditions. Show more

Keywords: Equality algebra, node, nodal filter, seminode, hertz algebra

DOI: 10.3233/JIFS-182860

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1457-1466, 2019

Authors: Fahandezi Sadi, Majid | Ansari, Ebrahim | Afsharchi, Mohsen

Article Type: Research Article

Abstract:  Supervised Word Sense Disambiguation (WSD) systems use features of the target word and its context to learn about all possible samples in an annotated dataset. Recently, word embeddings have emerged as a powerful feature in many NLP tasks. In supervised WSD, word embeddings can be used as a high-quality feature representing the context of an ambiguous word. In this paper, four improvements to existing state-of-the-art WSD methods are proposed. First, we propose a new model for assigning vector coefficients for a more precise context representation. Second, we apply a PCA dimensionality reduction process to find a better transformation of feature …matrices and train a more informative model. Third, a new weighting scheme is suggested to tackle the problem of unbalanced data in standard WSD datasets and finally, a novel idea is presented to combine word embedding features extracted from different independent corpora, which uses a voting aggregator among available trained models. All of these proposals individually improve disambiguation performance on Standard English lexical sample tasks, and using the combination of all proposed ideas makes a significant improvement in the accuracy score. Show more

Keywords: Word sense disambiguation, Word embedding, Supervised learning, Support vector machine

DOI: 10.3233/JIFS-182868

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1467-1476, 2019

Authors: Wang, Guijun | Gao, Jiansi

Article Type: Research Article

Abstract: Simple binary coded genetic algorithm (GA) and particle swarm optimization (PSO) fall easily into local minimums and fail to find the global optimal solution to the algorithm. Thus, the development of a hybrid algorithm between GA and PSO is urgently demanded. In this paper, a three-layer polygonal fuzzy neural network (PFNN) model and its error function are first given by the arithmetic operations of the polygonal fuzzy numbers. Second, the random sequences are constructed by a chaos random generator, these random sequences are used as the initial population of chaos GA and the optimal individuals for sub-populations gained by chaos …search are used as the initial population of PSO, and then an new parallel conjugate gradient-particle swarm optimization (PCG-PSO) is designed. Finally, a case study shows the proposed parallel CG-PS algorithm not only avoids dependence of traditional GA on initial values and overcomes the poor global optimization capability of traditional PSO, but also possesses advantages of rapid convergence and high stability. Show more

Keywords: Polygonal fuzzy number, polygonal fuzzy neural network, chaos genetic algorithm, particle swarm optimization, parallel conjugate gradient-particle swarm optimization

DOI: 10.3233/JIFS-182882

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1477-1489, 2019

Authors: Jani, Kuntesh K. | Srivastava, Subodh | Srivastava, Rajeev

Article Type: Research Article

Abstract: One of the most common lesions of the gastrointestinal tract (GIT) is an ulcer. Capsule endoscopy (CE) is a recent advancement in the field of gastroenterology for diagnosis of GIT abnormalities. However, CE video length ranges from 6 to 8 hours generating approximately 60000 images. For a medical expert, examination of such lengthy videos is time-consuming and tiresome. Also, the accuracy of diagnosis will largely depend upon individual expertise. A computer-aided diagnosis (CAD) system can significantly improve accuracy and reduce diagnosis time. In the proposed automated ulcer detection system, relevant features of the histogram of oriented gradients (HOG) and uniform …local binary patterns (LBP) are optimally selected by high variance low correlation (HVLC) based novel feature selection technique and the classification task is performed using support vector machine (SVM). Proposed feature selection technique reduces the feature set by 96.53% and outperforms five other state of the art feature selection techniques. The performance of proposed system is compared with other systems and it performs with accuracy, F measure and sensitivity of 95%, 95.12%, and 97.5% respectively. Show more

Keywords: Automated ulcer detection, CAD, capsule endoscopy, feature selection, HVLC

DOI: 10.3233/JIFS-182883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1491-1498, 2019

Authors: Xing, Zhikai | Jia, Heming | Song, Wenlong

Article Type: Research Article

Abstract: Considering that the 3D pulse-coupled neural network (3D-PCNN) model has the deficiency of high parameter complexity and low accuracy in color image segmentation, swarm intelligence optimization algorithm is adopted to optimize the image segmentation process. In this paper, whale optimization algorithm (WOA) is adopted to optimize the 3D-PCNN model parameters E and β . The improved product cross entropy (IPCE) is chosen as the fitness function of optimization algorithm. WOA algorithm is used to find the minimum fitness function, and the corresponding optimal parameters are obtained. Through the study of image segmentation in the image segmentation library of University of …Berkeley and the actual plant canopy image, the maximum entropy value and the Tsallis entropy value are compared and analyzed. Experimental results illustrate that the proposed algorithm can obtain more accurate image segmentation effect and higher segmentation rate. Show more

Keywords: 3D-PCNN, color image segmentation, whale optimization algorithm, improved product cross entropy

DOI: 10.3233/JIFS-182893

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1499-1511, 2019

Authors: Zuo, Wen-Jin | Li, Deng-Feng | Yu, Gao-Feng | Zhang, Li-Ping

Article Type: Research Article

Abstract: With the development of modern property service industry, the property perceived service quality (PPSQ) evaluation data is characterized by multiple evaluation subjects, complicated data structure and large scale data. Since the traditional decision-making methods are difficult to solve the above similar problems, this paper proposes a large group decision-making (LGDM) method of generalized multi-attribute and multi-scale (MAMS) based on the linear programming technique for multidimensional analysis of preference (LINMAP). In this method, the large-scale heterogeneous data of expert preference and user evaluation is fused. The decision matrix of generalized MAMS is used to process user evaluation information. The positive ideal …solution (PIS) and the attribute weights are determined by the LINMAP model. The comprehensive evaluation values are calculated and hereby the alternatives are ranked order. According to the relation between attribute weights and preset values, a mechanism for identifying invalid data is designed. This paper analyzes a set of survey data of PPSQ for the four public construction projects in the same city. The analysis results show the validity and rationality of the proposed method, and develop the property service evaluation theory. Show more

Keywords: Large group decision-making, generalized multi-attribute and multi-scale method, linear programming technique for multidimensional analysis of preference, large-scale heterogeneous data processing, property perceived service quality

DOI: 10.3233/JIFS-182934

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1513-1527, 2019

Authors: Abbas, Syed Zaheer | Ali Khan, Muhammad Sajjad | Abdullah, Saleem | Sun, Huafei | Hussain, Fawad

Article Type: Research Article

Abstract: Pythagorean fuzzy sets (PFSs) and interval-valued Pythagorean fuzzy sets (IVPFSs) play a vital role in decision-making processes. In this paper based on PFS and IVPFS we introduce the concept of Cubic Pythagorean fuzzy set in which membership degree is an IVPFS and non-membership degree is a PFS. We define some basic operation of Cubic Pythagorean fuzzy numbers (CPFNs). We define score and accuracy functions to compare CPFNs. We also define distance between CPFNs. Based on the defined operations we develop Cubic Pythagorean fuzzy weighted averaging (CPFWA) operator and Cubic Pythagorean fuzzy weighted geometric (CPFWG) operator. We discuss some properties of …the developed operators such as idempotancy, boundedness and monotonicity. Moreover, we give a multi-attribute decision making, to show the validity and effectiveness of the developed approach. Finally, we compare our approach with the existing methods. Show more

Keywords: Pythagorean fuzzy sets, interval-valued Pythagorean fuzzy sets, Cubic Pythagorean fuzzy sets, Cubic Pythagorean fuzzy weighted averaging (CPFWA) operator, Cubic Pythagorean fuzzy weighted geometric (CPFWG) operator, decision making

DOI: 10.3233/JIFS-18382

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1529-1544, 2019

Authors: Rahman, Atta

Article Type: Research Article

Abstract: In this paper, a numerical solution to the Troesch problem using a memetic computing technique is proposed. In this regard, a linear combination of Gaussian radial basis functions (GRBF) as approximate mathematical framework is suggested. A set of unknown yet adaptable parameters are modeled in a cost function, representing the trial solution. Differential Evolution (DE) algorithm crossed with Interior Point algorithm (IPA) and Pattern Search (PS) are utilized to find the unknowns. Numerical results based on three special cases of proposed scheme are compared with the exact solution as well as many other numerical and classical approximation methods. Analysis reveals …that the proposed scheme is promising in terms of accuracy and conformation to the exact solution. Show more

Keywords: Troesch problem, differential evolution, gaussian radial basis function, boundary value problem, pattern search (PS), interior point algorithm (IPA), memetic computing (MC)

DOI: 10.3233/JIFS-18579

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1545-1554, 2019

Authors: Zhang, Haidong | He, Yanping | Ma, Weiyuan

Article Type: Research Article

Abstract: Through a combination of hesitant fuzzy sets with rough sets, this study develops a single-granulation hesitant fuzzy rough set model from the perspective of granular computing. In the multi-granulation framework, we propose two types of multi-granulation rough set model, called the optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets. In the models, the multi-granulation hesitant fuzzy lower and upper approximations are defined based on multiple hesitant fuzzy tolerance relations. The relationships among the single-granulation hesitant fuzzy rough sets, optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets are also investigated. Finally, …we develop an approximation reduction approach of multi-granulation hesitant fuzzy rough sets to eliminate redundant hesitant fuzzy granulations with a detailed example. Show more

Keywords: Single-granulation hesitant fuzzy rough set, Multi-granulation hesitant fuzzy rough set, Hesitant fuzzy granulations, Approximation reduction

DOI: 10.3233/JIFS-18586

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1555-1567, 2019

Authors: Wang, Fang | Li, Xiao-Tong | Zhao, Jin | Chen, Shao-Hua

Article Type: Research Article

Abstract: The multiple attribute decision making (MADM) with interval grey uncertain linguistic (IGUL) is a topic of current interest, and various methods have been developed. However, few approaches taking the behavioral characteristics of the decision maker into account. In this paper, an extension of TODIM (i.e., an acronym in Portuguese of interactive and multiple attribute decision making) method, in which three behavioral characteristics of the decision maker (i.e., risk aversion, reference dependence and loss aversion) are considered, is proposed. First, the δ -Hamming distance is defined to deal with the interval grey uncertain linguistic variables by considering the level of the …decision maker’s risk aversion, and its distinguish ability is validated by compared to the classical Hamming distance. Then, the details of the TODIM· SIR method is demonstrated: (i) considering the reference dependence behaviour of the decision maker, the positive-ideal alternative (i.e., PIA ) and the negative-ideal alternative (i.e., NIA ) are defined, and the gain and loss degrees of each alternative relative to NIA and PIA are computed based on the δ -Hamming distance; (ii) taking the loss aversion behaviour of the decision maker into account, the perceived dominance degree of the decision maker for the gain and the loss is calculated; (iii) according to the idea of the Superiority and Inferiority Ranking method (i.e., SIR, an outranking method), the Gain-flow and the Loss-flow are defined, and the partial ranking orders and the complete ranking order are obtained. Finally, two numerical examples are given to illustrate the robustness and validity of the method, and a comparative analysis is also conducted to compare the TODIM· SIR method with both the classical TODIM method and the classical SIR method. Show more

Keywords: TODIM, SIR, Multiple attribute decision making, interval grey uncertain linguistic

DOI: 10.3233/JIFS-18654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1569-1581, 2019