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010   $a9783031603501$b(electronic bk.)
010   $z9783031603495
024 7 $a10.1007/978-3-031-60350-1
035   $a(MiAaPQ)EBC31502879
035   $a(Au-PeEL)EBL31502879
035   $a(CKB)32460313600041
035   $a(DE-He213)978-3-031-60350-1
035   $a(OCoLC)1443080821
035   $a(EXLCZ)9932460313600041
100   $a20240625d2024      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aGranularities-Driven Hesitant Fuzzy Linguistic Decision Making /$fby Yuanhang Zheng, Zeshui Xu
205   $a1st ed. 2024.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024.
215   $a1 online resource (201 pages)
225 1 $aStudies in Fuzziness and Soft Computing,$x1860-0808 ;$v433
311 08$aPrint version: Zheng, Yuanhang Granularities-Driven Hesitant Fuzzy Linguistic Decision Making Cham : Springer,c2024 9783031603495 
327   $a1. 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.
330   $aThis book introduces a state-of-the-art extension of fuzzy sets that is hesitant fuzzy linguistic term sets with granularity levels, and based on the fuzzy technique, several granularities-driven hesitant fuzzy linguistic decision-making methods are introduced to provide powerful tools to solve actual problems. Motivated from the idea of granular computing, the technique of hesitant fuzzy linguistic term sets with granularity levels is constructed, which not only brings flexibility and individuality for the linguistic model, but also provides a possibility to process a large amount of linguistic information in group decision-making efficiently and accurately. Thus, the researches on granularities-driven hesitant fuzzy linguistic decision making, can provide an effective way to solve practical decision-making problems based on complex linguistic information, and enrich the research system of decision-making and granular computing in theory and practice. In specific, this book introduces the construction of hesitant fuzzy linguistic term sets with granularity levels, and methods of handling attribute dependence, attribute reduction, single-objective group decision-making, and bi-objective group decision-making. The above decision-making methods are applied to the evaluation of medical and health management, and the effectiveness and advantages of the methods are verified by simulation comparison and analysis. Therefore, this book has not only important theoretical significance, but also broad application prospects.
410  0$aStudies in Fuzziness and Soft Computing,$x1860-0808 ;$v433
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aComputational Intelligence
606   $aArtificial Intelligence
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
676   $a006.3
700   $aZheng$b Yuanhang$01770354
701   $aXu$b Zeshui$0871861
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9910866574503321
996   $aGranularities-Driven Hesitant Fuzzy Linguistic Decision Making$94250397
997   $aUNINA