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Fuzzy Collaborative Forecasting and Clustering: Methodology, System Architecture, and Applications
Kategorie Beschreibung
036aXA-DE
037beng
087q978-3-030-22573-5
100 Chen, Tin-Chih Toly ¬[VerfasserIn]¬
104aHonda, Katsuhiro ¬[VerfasserIn]¬
331 Fuzzy Collaborative Forecasting and Clustering
335 Methodology, System Architecture, and Applications
403 1st ed. 2020
410 Cham
412 Springer
425 2020
425a2020
433 1 Online-Ressource (IX, 89 p. 42 illus., 9 illus. in color)
451bSpringerBriefs in Applied Sciences and Technology
527 Erscheint auch als (Druck-Ausgabe)ISBN: 978-3-030-22573-5
540aISBN 978-3-030-22574-2
700 |COM004000
700 |UYQ
700 |UYQ
700 |TEC009000
700b|006.3
700c|Q342
750 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
753 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
012 1668650088
081 Fuzzy Collaborative Forecasting and Clustering
100 Springer E-Book
125aElektronischer Volltext - Campuslizenz
655e$uhttps://doi.org/10.1007/978-3-030-22574-2
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