Fuzzy Collaborative Forecasting and Clustering von Tin-Chih Toly Chen | Methodology, System Architecture, and Applications | ISBN 9783030225735

Fuzzy Collaborative Forecasting and Clustering

Methodology, System Architecture, and Applications

von Tin-Chih Toly Chen und Katsuhiro Honda
Mitwirkende
Autor / AutorinTin-Chih Toly Chen
Autor / AutorinKatsuhiro Honda
Buchcover Fuzzy Collaborative Forecasting and Clustering | Tin-Chih Toly Chen | EAN 9783030225735 | ISBN 3-030-22573-9 | ISBN 978-3-030-22573-5

“This slim book by Chen and Honda provides readers with new developments in collaborative forecasting and clustering through techniques based on fuzzy logic. … The book and included research results are highly specialized. However, as it is organized in a coherent way, it is inspiring for further research on the topic. …. the book is recommended for researchers in collaborative ML who want a quick look at collaboration mechanisms via special prediction and clustering techniques based on fuzzy logic.” (Corrado Mencar, Computing Reviews, June 14, 2021)

Fuzzy Collaborative Forecasting and Clustering

Methodology, System Architecture, and Applications

von Tin-Chih Toly Chen und Katsuhiro Honda
Mitwirkende
Autor / AutorinTin-Chih Toly Chen
Autor / AutorinKatsuhiro Honda
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.