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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Fuzzy Collaborative Forecasting and Clustering/ by Tin-Chih Toly Chen, Katsuhiro Honda.
Reminder of title:	Methodology, System Architecture, and Applications /
Author:	Chen, Tin-Chih Toly.
other author:	Honda, Katsuhiro.
Description:	IX, 89 p. 42 illus., 9 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	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 /
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