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Granularities-driven hesitant fuzzy linguistic decision making

Record Type:	Electronic resources : Monograph/item
Title/Author:	Granularities-driven hesitant fuzzy linguistic decision makingby Yuanhang Zheng, Zeshui Xu.
Author:	Zheng, Yuanhang.
other author:	Xu, Zeshui.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xiv, 188 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Fuzzy decision making.
Online resource:	https://doi.org/10.1007/978-3-031-60350-1
ISBN:	9783031603501$q(electronic bk.)

Granularities-driven hesitant fuzzy linguistic decision making
Zheng, Yuanhang.

Granularities-driven hesitant fuzzy linguistic decision making[electronic resource] /by Yuanhang Zheng, Zeshui Xu. - Cham :Springer Nature Switzerland :2024. - xiv, 188 p. :ill. (chiefly col.), digital ;24 cm. - Studies in fuzziness and soft computing,v. 4331860-0808 ;. - Studies in fuzziness and soft computing ;v.273..

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.

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.

ISBN: 9783031603501$q(electronic bk.)

Standard No.: 10.1007/978-3-031-60350-1doiSubjects--Topical Terms:

346451
Fuzzy decision making.

LC Class. No.: QA279.6

Dewey Class. No.: 519.542

Granularities-driven hesitant fuzzy linguistic decision making
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505 0 $a 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.
520 $a 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.
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