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020 _a9789819931699
_9978-981-99-3169-9
024 7 _a10.1007/978-981-99-3169-9
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
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072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
_223
100 1 _aXu, Yejun.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aDeriving Priorities from Incomplete Fuzzy Reciprocal Preference Relations
_h[electronic resource] :
_bTheories and Methodologies /
_cby Yejun Xu.
250 _a1st ed. 2023.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2023.
300 _aXI, 174 p. 1 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 1. Introduction -- Chapter 2. Normalizing Rank Aggregation-based Method -- Chapter 3. Eigenvector Method -- Chapter 4. Logarithmic Least Squares Method -- Chapter 5. A Chi-Square Method -- Chapter 6. A Least Deviation Method -- Chapter 7. Priorities from Fuzzy Best Worst Method Matrix -- Chapter 8. Weighted Least Square Method -- Chapter 9. Priorities from Incomplete Hesitant Fuzzy Reciprocal Preference Relations.
520 _aAs we know, multiplicative preference relations (or called pairwise comparisons in AHP) were proposed by Dr. Thomas L Saaty. One important work is to derive its priority from pairwise comparisons. It has been proposed many methods to derive priority for multiplicative preference relation. On the basis of fuzzy sets, the fuzzy reciprocal preference relation is proposed and is extended to the incomplete contexts. However, how to derive the priorities from incomplete fuzzy reciprocal preference relations is an interesting and challenging work. This book systematically presents the theories and methodologies for deriving priorities from incomplete fuzzy reciprocal preference relations. This book can be divided into three parts. In the first part, this book introduces the basic concepts of fuzzy reciprocal preference relations and incomplete fuzzy reciprocal preference relations. Then, two consistencies of complete fuzzy reciprocal preference relations are introduced: additive consistency and multiplicative consistency. Then, the relationships between the fuzzy reciprocal elements and the weights are showed. Afterward, in the second part, different priority methods are presented. The inconsistency repairing procedures are also proposed. Last, the priority method for incomplete hesitant fuzzy reciprocal preference relations is presented. This book can be used as a reference for researchers in the areas of management science, information science, systems engineering, operations research, and other relevant fields. It can also be employed as a textbook for upper-level undergraduate students and graduate students.
650 0 _aArtificial intelligence.
650 0 _aComputer science.
650 0 _aInformation modeling.
650 0 _aMachine theory.
650 0 _aAlgorithms.
650 1 4 _aArtificial Intelligence.
650 2 4 _aModels of Computation.
650 2 4 _aInformation Model.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aDesign and Analysis of Algorithms.
650 2 4 _aComputer Science Logic and Foundations of Programming.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819931682
776 0 8 _iPrinted edition:
_z9789819931705
776 0 8 _iPrinted edition:
_z9789819931712
856 4 0 _uhttps://doi.org/10.1007/978-981-99-3169-9
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