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Fuzzy sets, rough sets, multisets an...

Torra, Vicenc.

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Fuzzy sets, rough sets, multisets and clustering

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fuzzy sets, rough sets, multisets and clustering/ edited by Vicenc Torra, Anders Dahlbom, Yasuo Narukawa.
other author:	Torra, Vicenc.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	x, 347 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	On 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.
Contained By:	Springer eBooks
Subject:	Fuzzy sets. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-47557-8
ISBN:	9783319475578

Fuzzy sets, rough sets, multisets and clustering
Fuzzy sets, rough sets, multisets and clustering[electronic resource] /edited by Vicenc Torra, Anders Dahlbom, Yasuo Narukawa. - Cham :Springer International Publishing :2017. - x, 347 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6711860-949X ;. - Studies in computational intelligence ;v.671..

On 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.

This 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.

ISBN: 9783319475578

Standard No.: 10.1007/978-3-319-47557-8doiSubjects--Topical Terms:

562997
Fuzzy sets.

LC Class. No.: QA248

Dewey Class. No.: 511.3223

Fuzzy sets, rough sets, multisets and clustering
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245 0 0 $a Fuzzy sets, rough sets, multisets and clustering $h [electronic resource] / $c edited by Vicenc Torra, Anders Dahlbom, Yasuo Narukawa.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a x, 347 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.671
505 0 $a On 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 $a This 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 $a Fuzzy sets. $3 562997
650 0 $a Rough sets. $3 577805
650 0 $a Cluster set theory. $3 753049
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
700 1 $a Torra, Vicenc. $3 1004861
700 1 $a Dahlbom, Anders. $3 3220546
700 1 $a Narukawa, Yasuo. $3 1004860
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.671. $3 3220547
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-47557-8
950 $a Engineering (Springer-11647)