scholarly journals Intuitionistic Fuzzy Entropy for Group Decision Making of Water Engineering Project Delivery System Selection

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1101 ◽  
Author(s):  
Liu ◽  
Qian ◽  
Lin ◽  
Zhang ◽  
Zhu
Keyword(s):  
Delivery System ◽  
Group Decision ◽  
Weighted Average ◽  
Fuzzy Entropy ◽  
Project Delivery ◽  
Delivery Mode ◽  
Practical Case ◽  
Engineering Project ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy

The project delivery mode is an extremely important link in the life cycle of water engineering. Many cases show that increases in the costs, construction period, and claims in the course of the implementation of water engineering are related to the decision of the project delivery mode in the early stages. Therefore, it is particularly important to choose a delivery mode that matches the water engineering. On the basis of identifying the key factors that affect the decision on the project delivery system and establishing a set of index systems, a comprehensive decision of engineering transaction is essentially considered to be a fuzzy multi-attribute group decision. In this study, intuitionistic fuzzy entropy was used to determine the weight of the influencing factors on the engineering transaction mode; then, intuitionistic fuzzy entropy was used to determine the weight of decision experts. Thus, a comprehensive scheme-ranking model based on an intuitionistic fuzzy hybrid average (IFHA) operator and intuitionistic fuzzy weighted average (IFWA) operator was established. Finally, a practical case analysis of a hydropower station further demonstrated the feasibility, objectivity, and scientific nature of the decision model.

scholarly journals Contingency Response Decision of Network Public Opinion Emergencies based on Intuitionistic Fuzzy Entropy and Preference Information of Decision Makers

2021 ◽  
Author(s):  
Sha Fu ◽  
Ye-zhi Xiao ◽  
Hang-jun Zhou
Keyword(s):  
Decision Making ◽  
Public Opinion ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Preference Information ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making ◽  
Network Public Opinion

Abstract A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuitionistic fuzzy group decision-making problem where the decision-makers weight and attribute weight are completely unknown and the decision-maker has preference information for the scheme. Firstly, an intuitionistic fuzzy interval judgment matrix is established to describe the original data of the key decision indicators for multiple network public opinion emergencies that erupt simultaneously. Secondly, the attribute weights are determined based on the improved intuitionistic fuzzy entropy construction method, and the expert weights are determined by using objective decision information, taking into account the intuitionistic fuzzy entropy of decision matrix. Thirdly, a scheme preference model and an attribute weight optimization model are established to determine the ranking method of intuitionistic fuzzy interval values. Then, an improved intuitionistic fuzzy number distance measure is introduced to make the evaluation result more accurate and reasonable when it comes to solving the deviation between the evaluation value and ideal solution of each scheme. Finally, the effectiveness and practicability of the proposed decision-making method are verified by an example of emergency crisis severity, which improves the efficiency of emergency treatment, helps emergency departments to better deal with the network public opinion crisis, improves the ability of public opinion guidance and control, and provides a new method and idea for multi-attribute intuitionistic fuzzy group decision-making problem.

On intuitionistic fuzzy order-α divergence and entropy measures with MABAC method for multiple attribute group decision-making

2021 ◽  
Vol 40 (1) ◽  
pp. 1191-1217
Author(s):  
Rajkumar Verma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Information Measures ◽  
Divergence Measures ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Entropy Measures

The development of information measures associated with fuzzy and intuitionistic fuzzy sets is an important research area from the past few decades. Divergence and entropy are two significant information measures in the intuitionistic fuzzy set (IFS) theory, which have gained wider attention from researchers due to their extensive applications in different areas. In the literature, the existing information measures for IFSs have some drawbacks, which make them irrelevant to use in application areas. In order to obtain more robust and flexible information measures for IFSs, the present work develops and studies some parametric information measures under the intuitionistic fuzzy environment. First, the paper reviews the existing intuitionistic fuzzy divergence measures in detail with their shortcomings and then proposes four new order-α divergence measures between two IFSs. It is worth mentioning that the developed divergence measures satisfy several elegant mathematical properties. Second, we define four new entropy measures called order-α intuitionistic fuzzy entropy measures in order to quantify the fuzziness associated with an IFS. We prove basic and advanced properties of the order-α intuitionistic fuzzy entropy measures for justifying their validity. The paper shows that the introduced measures include various existing fuzzy and intuitionistic fuzzy information measures as their special cases. Further, utilizing the conventional multi-attributive border approximation area comparison (MABAC) model, we develop an intuitionistic fuzzy MABAC method to solve real-life multiple attribute group decision-making problems. Finally, the proposed method is demonstrated by using a practical application of personnel selection.

scholarly journals An Intelligent Group Decision Evaluation Model with Interval-Valued Intuitionistic Fuzzy Entropy Technology for Microblog User Influence

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Lihua Zeng ◽  
Tonghua Yang ◽  
Haiping Ren ◽  
Neal Xiong
Keyword(s):  
Social Network ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Fuzzy Entropy ◽  
Evaluation Index System ◽  
Intuitionistic Fuzzy ◽  
User Influence ◽  
Intuitionistic Fuzzy Entropy ◽  
The Impact ◽  
Interval Valued

Aiming at the shortcomings of some existing interval-valued intuitionistic fuzzy entropy, this paper proposes an interval-valued intuitionistic fuzzy entropy, which contains not only the interval distance between membership and nonmembership but also the average hesitancy information. On this basis, the impact evaluation of microblog users is studied. Through the multilevel decomposition of user influence, the coverage of microblog, user interaction, and user activity are constructed as the first level indicators, and nine secondary indicators are selected as the comprehensive evaluation index system of microblog influence. Considering the highly dynamic and unstructured characteristics of social network data, the idea of interval-valued intuitionistic fuzzy is introduced to transform the evaluation of social network users’ influence into interval-valued intuitionistic fuzzy multiattribute group decision-making problem. Finally, the model is applied to dynamic evaluation of Sina Weibo users’ influence to verify the effectiveness of the model.

scholarly journals Assessing Customer Satisfaction of Urban Rail Transit Network in Tianjin Based on Intuitionistic Fuzzy Group Decision Model

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yuning Wang ◽  
Zhe Zhang ◽  
Hui Sun
Keyword(s):  
Customer Satisfaction ◽  
Decision Model ◽  
Group Decision ◽  
Urban Rail Transit ◽  
Fuzzy Entropy ◽  
Rail Transit ◽  
Satisfaction Level ◽  
Intuitionistic Fuzzy ◽  
Urban Rail ◽  
Intuitionistic Fuzzy Entropy

Urban rail transit has played an important role in big and crowded cities. Providing services with high levels of customer satisfaction is essential in order to increase the sharing rate of urban rail transit and to reduce traffic congestion by shifting people away from private car use. Therefore, it is of great significance to improve the customer satisfaction of urban rail transit. This paper presents an intuitionistic fuzzy group decision model to evaluate the customer satisfaction of urban rail transit. An evaluation indicator system including seven categories of indicators is established to measure passengers’ satisfaction. The overall customer satisfaction level of the urban rail transit lines is obtained by the intuitionistic fuzzy entropy and intuitionistic fuzzy weighted average (IFWA) operator. The intuitionistic fuzzy entropy is used to solve attribute weights and IFWA operator is used to solve the information aggregation. Drawing on Tianjin urban rail transit lines as a case study, the detailed analyses were conducted to evaluate the overall customer satisfaction level of five urban rail transit lines and as such suggesting remedy strategies. The results can help urban rail transit operation company to improve the service quality of urban rail transit.

Generalized Choquet Integral Operator of Triangular Atanassov’s Intuitionistic Fuzzy Numbers and Application to Multi-Attribute Group Decision Making

2016 ◽  
Vol 24 (05) ◽  
pp. 647-683 ◽  
Author(s):  
Jiu-Ying Dong ◽  
Li-Lian Lin ◽  
Feng Wang ◽  
Shu-Ping Wan
Keyword(s):  
Decision Making ◽  
Integral Operator ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Weighted Average ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Goal Programming Model ◽  
Ordered Weighted Average

The purpose of this paper is to propose a new approach to interactive multi-attribute group decision making with triangular Atanassov's intuitionistic fuzzy numbers (TAIFNs). The contribution of this study is fivefold: (1) Minkowski distance between TAIFNs is firstly defined; (2) We define the possibility attitudinal expected values of TAIFNs and thereby present a novel risk attitudinal ranking method of TAIFNs which can sufficiently consider the risk attitude of decision maker; (3) The weighted average operator (TAIFWA) and generalized ordered weighted average (TAIFGWA) operator of TAIFNs are defined as well as the hybrid ordered weighted average (TAIFHOWA) operator; (4) To study the interaction between attributes, we further develop the generalized Choquet (TAIF-GC) integral operator and generalized hybrid Choquet (TAIF-GHC) integral operator of TAIFNs. Their desirable properties are also discussed; (5) The individual overall value of alternative is obtained by TAIF-GC operator and the collective one is derived through TAIFWA operator. Fuzzy measures of attribute subsets and expert weights are objectively derived through constructing multi-objective optimization model which is transformed into the goal programming model to solve. The system analyst selection example verifies effectiveness of the proposed approach.

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

Multi-Criteria Decision-Making Model using Intuitionistic Fuzzy Entropy and Variable Weight Theory

Mekatronika ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 18-25
Author(s):  
Omar Ayasrah ◽  
Faiz Mohd Turan
Keyword(s):  
Decision Making ◽  
Fuzzy Entropy ◽  
Decision Makers ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Variable Weight ◽  
Intuitionistic Fuzzy Entropy ◽  
Perform Sensitivity Analysis ◽  
Almost All

The aim of this research is to develop a new multi-criteria decision-making method that integrates an intuitionistic fuzzy entropy measure and variable weight theory to be implemented in different fields to provide a solution for MCDM problems when the available information is incomplete. A limited number of studies have considered determining decision maker’s weights by performing objective techniques, and almost all of these researches detected a constant weights for the decision makers. In addition, most of the MCDM studies were not formulated to perform sensitivity analysis. The new method is based on the TOPSIS model with an intuitionistic fuzzy entropy measure in the exponential-related function form and the engagement of the variable weight theory to determine weights for the decision-makers that vary as per attibutes. Lastly, a mathematical model was developed in this research to be as an input for developing the mobile-aplication based method in future for virtual use of the new MCDM method.

Kernel intuitionistic fuzzy entropy clustering for MRI image segmentation

2019 ◽  
Vol 24 (6) ◽  
pp. 4003-4026 ◽  
Author(s):  
Dhirendra Kumar ◽  
R. K. Agrawal ◽  
Hanuman Verma
Keyword(s):  
Image Segmentation ◽  
Fuzzy Entropy ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Mri Image
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