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020 _a9783319475578
_9978-3-319-47557-8
024 7 _a10.1007/978-3-319-47557-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aFuzzy Sets, Rough Sets, Multisets and Clustering
_h[electronic resource] /
_cedited by Vicenç Torra, Anders Dahlbom, Yasuo Narukawa.
246 3 _aa
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aX, 347 p. 40 illus., 15 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v671
505 0 _aOn this book: clustering, multisets, rough sets and fuzzy sets -- Part 1: Clustering and Classification -- Contributions of Fuzzy Concepts to Data Clustering -- Fuzzy Clustering/Co-clustering and Probabilistic Mixture Models-induced Algorithms -- Semi-Supervised Fuzzy c-Means Algorithms by Revising Dissimilarity/Kernel Matrices -- Various Types of Objective-Based Rough Clustering -- On Some Clustering Algorithms Based on Tolerance -- Robust Clustering Algorithms Employing Fuzzy-Possibilistic Product Partition -- Consensus-based agglomerative hierarchical clustering -- Using a reverse engineering type paradigm in clustering. An evolutionary pro-gramming based approach -- On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data -- Experiences using Decision Trees for Knowledge Discovery -- Part 2: Bags, Fuzzy Bags, and Some Other Fuzzy Extensions -- L-fuzzy Bags -- A Perspective on Differences between Atanassov’s Intuitionistic Fuzzy Sets and Interval-valued Fuzzy Sets -- Part 3: Rough Sets -- Attribute Importance Degrees Corresponding to Several Kinds of Attribute Reduction in the Setting of the Classical Rough Sets -- A Review on Rough Set-based Interrelationship Mining -- Part 4: Fuzzy sets and decision making -- OWA Aggregation of Probability Distributions Using the Probabilistic Exceedance Method -- A dynamic average value-at-risk portfolio model with fuzzy random variables -- Group Decision Making: Consensus Approaches based on Soft Consensus Measures -- Construction of capacities from overlap indexes -- Clustering alternatives and learning preferences based on decision attitudes and weighted overlap dominance.
520 _aThis book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aTorra, Vicenç.
_eeditor.
_0(orcid)0000-0002-0368-8037
_1https://orcid.org/0000-0002-0368-8037
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700 1 _aDahlbom, Anders.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_963450
700 1 _aNarukawa, Yasuo.
_eeditor.
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_1https://orcid.org/0000-0001-9928-1444
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_4http://id.loc.gov/vocabulary/relators/edt
_963451
710 2 _aSpringerLink (Online service)
_963452
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319475561
776 0 8 _iPrinted edition:
_z9783319475585
776 0 8 _iPrinted edition:
_z9783319837673
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v671
_963453
856 4 0 _uhttps://doi.org/10.1007/978-3-319-47557-8
912 _aZDB-2-ENG
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