Kooperativer Bibliotheksverbund

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Format: XIV, 188 p. 48 illus., 39 illus. in color. , online resource.

Edition: 1st ed. 2024.

ISBN: 9783031603501

Series Statement: Studies in Fuzziness and Soft Computing, 433

Content: This book introduces a state-of-the-art extension of fuzzy sets that is hesitant fuzzy linguistic term sets with granularity levels, and based on the fuzzy technique, several granularities-driven hesitant fuzzy linguistic decision-making methods are introduced to provide powerful tools to solve actual problems. Motivated from the idea of granular computing, the technique of hesitant fuzzy linguistic term sets with granularity levels is constructed, which not only brings flexibility and individuality for the linguistic model, but also provides a possibility to process a large amount of linguistic information in group decision-making efficiently and accurately. Thus, the researches on granularities-driven hesitant fuzzy linguistic decision making, can provide an effective way to solve practical decision-making problems based on complex linguistic information, and enrich the research system of decision-making and granular computing in theory and practice. In specific, this book introduces the construction of hesitant fuzzy linguistic term sets with granularity levels, and methods of handling attribute dependence, attribute reduction, single-objective group decision-making, and bi-objective group decision-making. The above decision-making methods are applied to the evaluation of medical and health management, and the effectiveness and advantages of the methods are verified by simulation comparison and analysis. Therefore, this book has not only important theoretical significance, but also broad application prospects.

Note: 1. Introduction -- 2. Hesitant fuzzy linguistic term set with granularity level -- 3. Attribute dependency processing based on hesitant fuzzy linguistic term sets with granularity levels -- 4. Attribute reduction procedure based on hesitant fuzzy linguistic term sets with granularity levels -- 5. Single-objective group decision making based on complete hesitant fuzzy linguistic term sets with granularity levels.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031603495

Additional Edition: Printed edition: ISBN 9783031603518

Additional Edition: Printed edition: ISBN 9783031603525

Language: English

DOI: 10.1007/978-3-031-60350-1

URL: https://doi.org/10.1007/978-3-031-60350-1

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (201 pages)

Edition: 1st ed.

ISBN: 9783031603501

Series Statement: Studies in Fuzziness and Soft Computing Series ; v.433

Note: Intro -- Preface -- Contents -- About the Authors -- 1 Introduction -- 1.1 Background -- 1.2 Literature Review of Hesitant Fuzzy Linguistic Group Decision Making -- 1.2.1 Literature Review on Hesitant Fuzzy Linguistic Term Sets -- 1.2.2 Literature Review on Group Decision Making -- 1.3 Aims and Focuses of This Book -- References -- 2 Hesitant Fuzzy Linguistic Term Set with Granularity Level -- 2.1 Complete Hesitant Fuzzy Linguistic Term Set with Granularity Level -- 2.1.1 Multiplicative Consistency of Hesitant Fuzzy Linguistic Preference Relation -- 2.1.2 Complete Hesitant Fuzzy Linguistic Term Set and Preference Relation with Granularity Level -- 2.1.3 Discussions -- 2.2 Incomplete Hesitant Fuzzy Linguistic Term Set with Granularity Level -- 2.2.1 Initial Consistency of Incomplete Hesitant Fuzzy Linguistic Preference Relation -- 2.2.2 Incomplete Hesitant Fuzzy Linguistic Term Set and Preference Relation with Granularity Level -- 2.2.3 Discussions -- 2.3 Conclusions -- References -- 3 Attribute Dependency Processing Based on Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 3.1 The Granulation Process of Hesitant Fuzzy Linguistic Term Sets When Attributes are Dependent -- 3.2 Analytic Network Process Based on Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 3.2.1 Construction of Decision Matrix Including Objective Data and Subjective Data -- 3.2.2 Obtaining the Initial Weights of Attributes by Subjective Methods -- 3.2.3 Constructing a Supermatrix to Obtain the Comprehensive Weights of Attributes -- 3.2.4 Flowchart Summary of the Proposed Method -- 3.3 Application to the Evaluation of Hierarchical Diagnosis and Treatment Scheme -- 3.3.1 Assessment Indicator System of the Hierarchical Medical Policy Proposals -- 3.3.2 Selection of Hierarchical Diagnosis and Treatment Alternatives. , 3.3.3 Deconstruction of the Multi-attribute Decision-Making Problems -- 3.3.4 Calculation Process -- 3.4 Comparison Analysis -- 3.4.1 Discussion and Analysis Based on Numerical Results -- 3.4.2 Discussion on Different Weights of the Length of Observation Time -- 3.4.3 Comparisons with Analytic Hierarchy Process Based on G-HFLPRs -- 3.5 Discussions -- 3.5.1 Discussion on Theoretical Viewpoint -- 3.5.2 Discussion on Application Viewpoint -- 3.6 Conclusions -- References -- 4 Attribute Reduction Procedure Based on Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 4.1 Attribute Reduction Based on Hesitant Fuzzy Linguistic Term Sets -- 4.1.1 Some Concepts and Operations -- 4.1.2 Attribute Reduction Procedure Based on Hesitant Fuzzy Linguistic Term Sets -- 4.2 Group Decision-Making Process Based on Linguistic Information with Granularity Level -- 4.2.1 Probabilistic Linguistic Preference Relations with Granularity Levels -- 4.2.2 Network Analysis Process Based on Probabilistic Linguistic Preference Relations with Granularity Levels -- 4.2.3 Group Decision-Making Process -- 4.3 Method Application -- 4.3.1 Health-Influencing Factors for Graduate Students -- 4.3.2 Process and Findings of Questionnaire Survey -- 4.3.3 Weight Calculation of Main Factors Affecting the Physical and Mental Health of Graduate Students -- 4.4 Comparison Analysis -- 4.5 Discussions -- 4.5.1 Theoretical Level -- 4.5.2 Application Aspects -- 4.6 Conclusions -- References -- 5 Single-objective Group Decision Making Based on Complete Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 5.1 Fuzzy C-Means Clustering Method Based on Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 5.2 Large-Scale Group Decision-Making Process -- 5.3 Method Application -- 5.3.1 Background -- 5.3.2 Calculation Process and Results -- 5.3.3 Comparison Analysis of Examples. , 5.4 Simulation Comparative Analysis -- 5.4.1 Validity of Information Granularity Levels -- 5.4.2 Superiority of the Consistency Measure and Improving Method -- 5.4.3 Superiority of the Fuzzy c-Means Clustering -- 5.5 Discussions -- 5.5.1 Theoretical Level -- 5.5.2 Application Aspect -- 5.6 Conclusions -- References -- 6 Single-objective Group Decision Making Based on Incomplete Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 6.1 A Completion Method for Incomplete Hesitant Fuzzy Linguistic Preference Relations with Granularity Levels -- 6.1.1 Incomplete HFLPR Has an Acceptable Initial Consistency -- 6.1.2 Incomplete HFLPR Has an Unacceptable Initial Consistency and is Modifiable -- 6.1.3 Incomplete HFLPR Does not Have Initial Consistency -- 6.2 Large-Scale Group Decision-Making Process -- 6.3 Method Application -- 6.4 Simulation Comparison Analysis -- 6.4.1 Superiority in Consistency Improving Process -- 6.4.2 Superiority in Completion Process -- 6.5 Discussions -- 6.5.1 Discussions from Theoretical Level -- 6.5.2 Discussions from Application Aspect -- 6.6 Conclusions -- References -- 7 Bi-objective Group Decision-Making Based on Hesitant Fuzzy Linguistic Term Sets with Granularity Levels -- 7.1 Construction of Bi-objective Group Decision-Making Model -- 7.1.1 Model Construction Roadmap -- 7.1.2 Bi-objective Function for the LSGDM Problem -- 7.2 Bi-objective Group Decision-Making Process Based on Hesitant Fuzzy Linguistic Preference Relations with Granularity Levels -- 7.2.1 Selecting Appropriate Decision Makers -- 7.2.2 Solving Bi-objective Clustering Model Based on Evolutionary Algorithm -- 7.2.3 Obtaining Group Decision-Making Results -- 7.3 Method Application -- 7.3.1 Description of the LSGDM Problem -- 7.3.2 Calculation Process and Results -- 7.4 Simulation Comparison Analysis -- 7.4.1 Validity Verification. , 7.4.2 Comparison with Single-objective Clustering Method -- 7.4.3 Comparison with Other LSGDM Methods -- 7.5 Discussions -- 7.5.1 Theoretical Layer -- 7.5.2 Application Layer -- 7.6 Conclusions -- References.

Additional Edition: Print version: Zheng, Yuanhang Granularities-Driven Hesitant Fuzzy Linguistic Decision Making Cham : Springer,c2024 ISBN 9783031603495

Language: English