國立虎尾科技大學 |

Fuzzy Collaborative Forecasting and Clustering = Methodology, System Architecture, and Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Fuzzy Collaborative Forecasting and Clustering/ by Tin-Chih Toly Chen, Katsuhiro Honda.
其他題名:	Methodology, System Architecture, and Applications /
作者:	Chen, Tin-Chih Toly.
其他作者:	Honda, Katsuhiro.
面頁冊數:	IX, 89 p. 42 illus., 9 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-22574-2
ISBN:	9783030225742

Fuzzy Collaborative Forecasting and Clustering = Methodology, System Architecture, and Applications /
Chen, Tin-Chih Toly.

Fuzzy Collaborative Forecasting and ClusteringMethodology, System Architecture, and Applications /[electronic resource] :by Tin-Chih Toly Chen, Katsuhiro Honda. - 1st ed. 2020. - IX, 89 p. 42 illus., 9 illus. in color.online resource. - SpringerBriefs in Applied Sciences and Technology,2191-530X. - SpringerBriefs in Applied Sciences and Technology,.

Fuzzy Collaborative Intelligence and Systems -- Linear Fuzzy Collaborative Forecasting Methods -- Nonlinear Fuzzy Collaborative Forecasting Methods -- Fuzzy Co-clustering -- Collaborative Framework for Fuzzy Co-clustering -- Three-mode Fuzzy Co-clustering -- Collaborative Framework for Three-mode Fuzzy Co-clustering.

This book introduces the basic concepts of fuzzy collaborative forecasting and clustering, including its methodology, system architecture, and applications. It demonstrates how dealing with disparate data sources is becoming more and more popular due to the increasing spread of internet applications. The book proposes the concepts of collaborative computing intelligence and collaborative fuzzy modeling, and establishes several so-called fuzzy collaborative systems. It shows how technical constraints, security issues, and privacy considerations often limit access to some sources. This book is a valuable source of information for postgraduates, researchers and fuzzy control system developers, as it presents a very effective fuzzy approach that can deal with disparate data sources, big data, and multiple expert decision making.

ISBN: 9783030225742

Standard No.: 10.1007/978-3-030-22574-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Fuzzy Collaborative Forecasting and Clustering = Methodology, System Architecture, and Applications /
LDR:02627nam a22003975i 4500 001 1017331
003 DE-He213
005 20200705204533.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030225742 $9 978-3-030-22574-2
024 7 $a 10.1007/978-3-030-22574-2 $2 doi
035 $a 978-3-030-22574-2
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Chen, Tin-Chih Toly. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1312103
245 1 0 $a Fuzzy Collaborative Forecasting and Clustering $h [electronic resource] : $b Methodology, System Architecture, and Applications / $c by Tin-Chih Toly Chen, Katsuhiro Honda.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a IX, 89 p. 42 illus., 9 illus. in color. $b online resource.
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 SpringerBriefs in Applied Sciences and Technology, $x 2191-530X
505 0 $a Fuzzy Collaborative Intelligence and Systems -- Linear Fuzzy Collaborative Forecasting Methods -- Nonlinear Fuzzy Collaborative Forecasting Methods -- Fuzzy Co-clustering -- Collaborative Framework for Fuzzy Co-clustering -- Three-mode Fuzzy Co-clustering -- Collaborative Framework for Three-mode Fuzzy Co-clustering.
520 $a This book introduces the basic concepts of fuzzy collaborative forecasting and clustering, including its methodology, system architecture, and applications. It demonstrates how dealing with disparate data sources is becoming more and more popular due to the increasing spread of internet applications. The book proposes the concepts of collaborative computing intelligence and collaborative fuzzy modeling, and establishes several so-called fuzzy collaborative systems. It shows how technical constraints, security issues, and privacy considerations often limit access to some sources. This book is a valuable source of information for postgraduates, researchers and fuzzy control system developers, as it presents a very effective fuzzy approach that can deal with disparate data sources, big data, and multiple expert decision making.
650 0 $a Computational intelligence. $3 568984
650 0 $a Data mining. $3 528622
650 0 $a Artificial intelligence. $3 559380
650 0 $a Sociophysics. $3 890761
650 0 $a Econophysics. $3 796705
650 0 $a Operations research. $3 573517
650 0 $a Decision making. $3 528319
650 0 $a Computer simulation. $3 560190
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Data-driven Science, Modeling and Theory Building. $3 1112983
650 2 4 $a Operations Research/Decision Theory. $3 669176
650 2 4 $a Simulation and Modeling. $3 669249
700 1 $a Honda, Katsuhiro. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 680053
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030225735
776 0 8 $i Printed edition: $z 9783030225759
830 0 $a SpringerBriefs in Applied Sciences and Technology, $x 2191-530X $3 1253575
856 4 0 $u https://doi.org/10.1007/978-3-030-22574-2
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)