03775nam a22004815i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050000900172072001600181072002300197072001500220100008500235245012300320250001800443264006900461300006500530336002600595337002600621338003600647347002400683490006300707505042000770520154301190650003902733650003602772650003902808650003602847700008002883710003402963773002602997776003603023776003603059776003603095830007003131856004603201912001403247912001503261999001703276978-3-031-60350-1DE-He21320251030112331.0cr nn 008mamaa240625s2024    sz |    s    |||| 0|eng d  a97830316035019978-3-031-60350-17 a10.1007/978-3-031-60350-12doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema1 aZheng, Yuanhang.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut97928310aGranularities-Driven Hesitant Fuzzy Linguistic Decision Makingh[electronic resource] /cby Yuanhang Zheng, Zeshui Xu.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXIV, 188 p. 48 illus., 39 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aStudies in Fuzziness and Soft Computing,x1860-0808 ;v4330 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.  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. 0aComputational intelligence.964052 0aArtificial intelligence.95844114aComputational Intelligence.96405224aArtificial Intelligence.9584411 aXu, Zeshui.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9792842 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303160349508iPrinted edition:z978303160351808iPrinted edition:z9783031603525 0aStudies in Fuzziness and Soft Computing,x1860-0808 ;v43396828540uhttps://doi.org/10.1007/978-3-031-60350-1  aZDB-2-INR  aZDB-2-SXIT  c61005d61005