Cover Image

Fuzzy sets, rough sets, multisets and clustering / Vicenç Torra, Anders Dahlbom, Yasuo Narukawa, editors.

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...

Full description

Saved in:
Bibliographic Details
Online Access: Full Text (via Springer)
Other Authors: Torra, Vicenç (Editor), Dahlbom, Anders (Editor), Narukawa, Yasuo (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, 2017.
Series:Studies in computational intelligence ; v. 671.
Subjects:
Fuzzy sets.
Rough sets.
Cluster set theory.

MARC

LEADER 00000cam a2200000xi 4500
001 b9056676
006 m o d
007 cr |||||||||||
008 170124s2017 sz a o 000 0 eng d
005 20240418151559.9
019 |a 974649514 
020 |a 9783319475578  |q (electronic bk.) 
020 |a 3319475576  |q (electronic bk.) 
020 |z 9783319475561  |q (print) 
024 7 |a 10.1007/978-3-319-47557-8 
035 |a (OCoLC)spr969844365 
035 |a (OCoLC)969844365  |z (OCoLC)974649514 
035 |a (OCoLC)969844365 
037 |a spr10.1007/978-3-319-47557-8 
040 |a GW5XE  |b eng  |e rda  |e pn  |c GW5XE  |d YDX  |d OCLCF  |d UAB  |d NJR  |d COO  |d UPM 
049 |a GWRE 
050 4 |a QA248 
245 0 0 |a Fuzzy sets, rough sets, multisets and clustering /  |c Vicenç Torra, Anders Dahlbom, Yasuo Narukawa, editors. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (x, 347 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent. 
337 |a computer  |b c  |2 rdamedia. 
338 |a online resource  |b cr  |2 rdacarrier. 
347 |a text file  |b PDF  |2 rda. 
490 1 |a Studies in computational intelligence,  |x 1860-949X ;  |v volume 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. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed January 24, 2017) 
650 0 |a Fuzzy sets.  |0 http://id.loc.gov/authorities/subjects/sh85052627. 
650 0 |a Rough sets.  |0 http://id.loc.gov/authorities/subjects/sh98004363. 
650 0 |a Cluster set theory.  |0 http://id.loc.gov/authorities/subjects/sh85027255. 
650 7 |a Cluster set theory.  |2 fast  |0 (OCoLC)fst00864990. 
650 7 |a Fuzzy sets.  |2 fast  |0 (OCoLC)fst00936812. 
650 7 |a Rough sets.  |2 fast  |0 (OCoLC)fst01100703. 
700 1 |a Torra, Vicenç,  |e editor.  |0 http://id.loc.gov/authorities/names/no2003087712  |1 http://isni.org/isni/0000000063030902. 
700 1 |a Dahlbom, Anders,  |e editor.  |0 http://id.loc.gov/authorities/names/nb2017003176. 
700 1 |a Narukawa, Yasuo,  |e editor.  |0 http://id.loc.gov/authorities/names/nb2004306604  |1 http://isni.org/isni/000000003863689X. 
776 0 8 |i Printed edition:  |z 9783319475561. 
830 0 |a Studies in computational intelligence ;  |v v. 671.  |0 http://id.loc.gov/authorities/names/no2005104439. 
856 4 0 |u https://colorado.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-47557-8  |z Full Text (via Springer) 
907 |a .b90566762  |b 03-19-20  |c 02-20-17 
998 |a web  |b 05-01-17  |c g  |d b   |e -  |f eng  |g sz   |h 0  |i 1 
907 |a .b90566762  |b 07-02-19  |c 02-20-17 
944 |a MARS - RDA ENRICHED 
907 |a .b90566762  |b 07-06-17  |c 02-20-17 
907 |a .b90566762  |b 05-23-17  |c 02-20-17 
915 |a I 
956 |a Springer e-books 
956 |b Springer Nature - Springer Engineering eBooks 2017 English International 
999 f f |i f7b1f5a3-393f-5cd9-805f-b921729891b4  |s 33df1c96-9306-5670-a4f5-abe511f3d3c8 
952 f f |p Can circulate  |a University of Colorado Boulder  |b Online  |c Online  |d Online  |e QA248  |h Library of Congress classification  |i Ebooks, Prospector  |n 1 

Similar Items