scholarly journals Cloud service reliability assessment approach based on multi-valued neutrosophic cross-entropy and entropy measures

Filomat ◽  
2018 ◽  
Vol 32 (8) ◽  
pp. 2793-2812 ◽  
Author(s):  
Yi Wang ◽  
Xiao-Kang Wang ◽  
Jian-Qiang Wang
Keyword(s):  
Decision Making ◽  
Reliability Assessment ◽  
Cloud Service ◽  
Cross Entropy ◽  
Distance Measures ◽  
Service Reliability ◽  
Entropy Measures ◽  
Assessment Approach ◽  
Criteria Weights ◽  
Better Than

Cloud service reliability assessment is a vital decision-making activity for companies and individuals. In this assessment, the evaluation information can be represented by multi-valued neutrosophic numbers (MVNNs). MVNNs are regarded as an integration of single-valued neutrosophic numbers (SVNNs) and hesitant fuzzy numbers (HFNs); therefore, considering the defects of entropy and crossentropy measures for SVNNs and HFNs, we first define a framework of entropy measures and a family of cross-entropy measures for MVNNs in this paper. Second, a novel extended VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method based on entropy and cross-entropy measures is developed to address the decision-making problems when information about criteria weights is absolutely unknown. Finally, we apply the proposed method to evaluate cloud service reliability; also, a sensitivity analysis and a comparative analysis are made to interpret the practicality and effectiveness of it. The results of analyses verify that the proposed method based on cross-entropy is much better than the methods using general distance measures.

The distance measures and cross-entropy based on complex fuzzy sets and their application in decision making

2020 ◽  
Vol 39 (3) ◽  
pp. 3351-3374
Author(s):  
Peide Liu ◽  
Zeeshan Ali ◽  
Tahir Mahmood
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Similarity Measures ◽  
Decision Makers ◽  
Cross Entropy ◽  
Distance Measures ◽  
Fuzzy Information ◽  
Information Measures ◽  
Entropy Measures ◽  
Magdm Problems

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

scholarly journals Improved Cross Entropy Measures of Single Valued Neutrosophic Sets and Interval Neutrosophic Sets and Their Multicriteria Decision Making Methods

2015 ◽  
Vol 15 (4) ◽  
pp. 13-26 ◽  
Author(s):  
Jun Ye
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Cross Entropy ◽  
Entropy Measure ◽  
Neutrosophic Sets ◽  
Multicriteria Decision ◽  
Entropy Measures ◽  
The Cross ◽  
Ranking Order ◽  
Interval Neutrosophic Sets

Abstract Due to some drawbacks of the cross entropy between Single Valued Neutrosophic Sets (SVNSs) in dealing with decision-making problems, the existing single valued neutrosophic cross entropy indicates an asymmetrical phenomenon or may produce an undefined (unmeaningful) phenomenon in some situations. In order to overcome these disadvantages, this paper proposes an improved cross entropy measure of SVNSs and investigates its properties, and then extends it to a cross entropy measure between interval neutrosophic sets (INSs). Furthermore, the cross entropy measures are applied to multicriteria decision making problems with single valued neutrosophic information and interval neutrosophic information. In decision making methods, through the weighted cross entropy measure between each alternative and the the ideal alternative, one can obtain the ranking order of all alternatives and the best one. The decision-making methods using the proposed cross entropy measures can efficiently deal with decision making problems with incomplete, indeterminate and inconsistent information which exist usually in real situations. Finally, two illustrative examples are provided to demonstrate the application and efficiency of the developed decision making approaches under single valued neutrosophic and interval neutrosophic environments.

scholarly journals Selecting Personnel with the Weighted Cross-Entropy TOPSIS of Hesitant Picture Fuzzy Linguistic Sets

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Xiao-Hui Wu ◽  
Lin Yang ◽  
Jie Qian
Keyword(s):  
Decision Making ◽  
Personnel Selection ◽  
Multicriteria Decision Making ◽  
Cross Entropy ◽  
Human Resource Department ◽  
Picture Fuzzy Set ◽  
Entropy Measures ◽  
Measurement Tools ◽  
Definition Of ◽  
Fuzzy Linguistic

Personnel selection is a key important role for the human resource department of organization, and hesitant picture fuzzy linguistic sets (HPFLSs) elaborated the advantages of both hesitant linguistic set and picture fuzzy set, which is more flexible and effective to solve the decision-making problems of personnel selection than other extension of fuzzy linguistic sets (FLSs). Cross-entropy, as effective measurement tools, is wildly used under fuzzy multicriteria decision-making (FMCDM) environment; thus, in order to elaborate the advantages of both cross-entropy and HPFLSs under FMCDM environment, the cross-entropy definition of HPFLSs is firstly given in this paper. Meanwhile, several novel cross-entropy measures between two HPFLSs are introduced, and their related properties are proved. Then, an approach based on the weighted cross-entropy measures and TOPSIS under hesitant picture fuzzy linguistic environment is proposed. Finally, the proposed method is applied to the real personnel’s selection, and the ranking results show that the proposed methods are practical and effective.

scholarly journals GRA and CRITIC Method for Intuitionistic Fuzzy Multiattribute Group Decision Making and Application to Development Potentiality Evaluation of Cultural and Creative Garden

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Quan-Song Qi
Keyword(s):  
Decision Making ◽  
Urban Space ◽  
Group Decision Making ◽  
Group Decision ◽  
Creative Industries ◽  
Distance Measures ◽  
Creative Industry ◽  
Intuitionistic Fuzzy ◽  
Industrial Parks ◽  
Criteria Weights

In recent years, cultural and creative industry park is becoming a kind of hot industry to promote industrial restructuring and to improve the quality of urban space. For this reason, cultural and creative industrial parks are planning to build across the country. Currently, cultural and creative industrial parks that develop better than others thank to the government’s overall planning, construction, marketing, and management. At the same time, the new cultural and creative industry parks face enormous challenges, such as how to have together the cultural and creative industries and related groups or how to have area cultural creativity. And it is frequently regarded as a multiattribute group decision-making (MAGDM) process. Thus, a novel MAGDM process is needed to tackle it. Depending on the conventional grey relational analysis (GRA) method and intuitionistic fuzzy sets (IFSs), this paper designs a novel intuitive distance-based IF-GRA method for development potentiality evaluation of cultural and creative garden. First of all, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing the CRITIC method. Afterwards, relying on novel distance measures between IFSs, the GRA method is extended to the IFSs to calculate assessment score of each alternative. Eventually, an application about development potentiality evaluation of cultural and creative garden and some comparative analysis is given. The results think that the designed method is useful for development potentiality evaluation of cultural and creative garden.

scholarly journals Cross Entropy Measures of Bipolar and Interval Bipolar Neutrosophic Sets and Their Application for Multi-Attribute Decision Making

2018 ◽  
Author(s):  
Surapati Pramanik ◽  
Partha Pratim Dey ◽  
Florentin Smarandache ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Cross Entropy ◽  
Neutrosophic Set ◽  
Membership Functions ◽  
Neutrosophic Sets ◽  
Entropy Measures ◽  
Multi Attribute Decision Making ◽  
Important Extension ◽  
The Ideal

Bipolar neutrosophic set is an important extension of bipolar fuzzy set. This set is a hybridization of bipolar fuzzy set and neutrosophic set. Every element of a bipolar neutrosophic set consists of three independent positive membership functions and three independent negative membership functions. In this paper, we develop cross entropy measures of bipolar neutrosophic sets and prove its properties. We also define cross entropy measures of interval bipolar neutrosophic sets and prove its properties. Thereafter, we develop two novel multi-attribute decision making methods based on the proposed cross entropy measures. In the decision making framework, we calculate the weighted cross entropy measures between each alternative and the ideal alternative to rank the alternatives and choose the best one. We solve two illustrative examples of multi-attribute decision making problems and compare the obtained result with the results of other existing methods to show the applicability and effectiveness of the developed method. In the end, the main conclusion and future scope of research are summarized.

A Multi Criteria Decision Making Method for Cloud Service Selection and Ranking

2018 ◽  
Vol 9 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Rakesh Ranjan Kumar ◽  
Chiranjeev Kumar
Keyword(s):  
Decision Making ◽  
User Satisfaction ◽  
Selection Process ◽  
Multiple Criteria Decision Making ◽  
Service Selection ◽  
Pairwise Comparison ◽  
Cloud Service ◽  
Cloud Services ◽  
Topsis Method ◽  
Criteria Weights

This article describes how with the rapid growth of cloud services in recent years, it is very difficult to choose the most suitable cloud services among those services that provide similar functionality. The quality of services (QoS) is considered the most significant factor for appropriate service selection and user satisfaction in cloud computing. However, with a vast diversity in the cloud services, selection of a suitable cloud service is a very challenging task for a customer under an unpredictable environment. Due to the multidimensional attributes of QoS, cloud service selection problems are treated as a multiple criteria decision-making (MCDM) problem. This study introduces a methodology for determining the appropriate cloud service by integrating the AHP weighing method with TOPSIS method. Using AHP, the authors define the architecture for selection process of cloud services and compute the criteria weights using pairwise comparison. Thereafter, with the TOPSIS method, the authors obtain the final ranking of the cloud service based on overall performance. A real-time cloud case study affirms the potential of our proposed methodology, when compared to other MCDM methods. Finally, a sensitivity analysis testifies the effectiveness and the robustness of our proposed methodology.

scholarly journals Fuzzy Entropy for Pythagorean Fuzzy Sets with Application to Multicriterion Decision Making

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Miin-Shen Yang ◽  
Zahid Hussain
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Entropy ◽  
Entropy Measure ◽  
Pythagorean Fuzzy Sets ◽  
Entropy Measures ◽  
Criteria Weights ◽  
Ranking Of Alternatives ◽  
Probabilistic Type ◽  
Multicriterion Decision Making

The concept of Pythagorean fuzzy sets (PFSs) was initially developed by Yager in 2013, which provides a novel way to model uncertainty and vagueness with high precision and accuracy compared to intuitionistic fuzzy sets (IFSs). The concept was concretely designed to represent uncertainty and vagueness in mathematical way and to furnish a formalized tool for tackling imprecision to real problems. In the present paper, we have used both probabilistic and nonprobabilistic types to calculate fuzzy entropy of PFSs. Firstly, a probabilistic-type entropy measure for PFSs is proposed and then axiomatic definitions and properties are established. Secondly, we utilize a nonprobabilistic-type with distances to construct new entropy measures for PFSs. Then a min–max operation to calculate entropy measures for PFSs is suggested. Some examples are also used to demonstrate suitability and reliability of the proposed methods, especially for choosing the best one/ones in structured linguistic variables. Furthermore, a new method based on the chosen entropies is presented for Pythagorean fuzzy multicriterion decision making to compute criteria weights with ranking of alternatives. A comparison analysis with the most recent and relevant Pythagorean fuzzy entropy is conducted to reveal the advantages of our developed methods. Finally, this method is applied for ranking China-Pakistan Economic Corridor (CPEC) projects. These examples with applications demonstrate practical effectiveness of the proposed entropy measures.

Distance-based Knowledge measure of Hesitant Fuzzy Linguistic Term Set with its application in Multi-criteria decision-making

2022 ◽  
Vol 11 (1) ◽  
pp. 0-0
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Fuzzy Entropy ◽  
Distance Measures ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Knowledge Measure ◽  
Entropy Measures ◽  
Linguistic Term ◽  
Fuzzy Linguistic

Motivated by the structural aspect of the probabilistic entropy, the concept of fuzzy entropy enabled the researchers to investigate the uncertainty due to vague information. Fuzzy entropy measures the ambiguity/vagueness entailed in a fuzzy set. Hesitant fuzzy entropy and hesitant fuzzy linguistic term set based entropy presents a more comprehensive evaluation of vague information. In the vague situations of multiple-criteria decision-making, entropy measure is utilized to compute the objective weights of attributes. The weights obtained due to entropy measures are not reasonable in all the situations. To model such situation, a knowledge measure is very significant, which is a structural dual to entropy. A fuzzy knowledge measure determines the level of precision in a fuzzy set. This article introduces the concept of a knowledge measure for hesitant fuzzy linguistic term sets (HFLTS) and show how it may be derived from HFLTS distance measures. Authors also investigate its application in determining the weights of criteria in multi-criteria decision-making (MCDM).

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