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Fuzzy Collaborative Forecasting and Clustering: Methodology, System...

by Chen, Tin-Chih Toly; Honda,... | PB | VeryGood
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Condition:
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May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend ... Read moreAbout condition
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eBay item number:145696355200
Last updated on 02 Sep, 2024 06:22:54 BSTView all revisionsView all revisions

Item specifics

Condition
Very Good
A book that has been read and does not look new, but is in excellent condition. No obvious damage to the book cover, with the dust jacket (if applicable) included for hard covers. No missing or damaged pages, no creases or tears, no underlining or highlighting of text, and no writing in the margins. Some identifying marks on the inside cover, but this is minimal. Very little wear and tear. See the seller’s listing for full details and description of any imperfections. See all condition definitionsopens in a new window or tab
Seller notes
“May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend ...
Binding
Paperback
Weight
0 lbs
Product Group
Book
IsTextBook
No
ISBN
9783030225735
Subject Area
Computers, Technology & Engineering
Publication Name
Fuzzy Collaborative Forecasting and Clustering : Methodology, System Architecture, and Applications
Publisher
Springer International Publishing A&G
Item Length
9.3 in
Subject
Engineering (General), Intelligence (Ai) & Semantics, Databases / Data Mining
Publication Year
2019
Series
Springerbriefs in Applied Sciences and Technology Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Tin-Chih Toly Chen, Katsuhiro Honda
Item Weight
16 Oz
Item Width
6.1 in
Number of Pages
IX, 89 Pages

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030225739
ISBN-13
9783030225735
eBay Product ID (ePID)
13038619337

Product Key Features

Number of Pages
IX, 89 Pages
Language
English
Publication Name
Fuzzy Collaborative Forecasting and Clustering : Methodology, System Architecture, and Applications
Publication Year
2019
Subject
Engineering (General), Intelligence (Ai) & Semantics, Databases / Data Mining
Type
Textbook
Author
Tin-Chih Toly Chen, Katsuhiro Honda
Subject Area
Computers, Technology & Engineering
Series
Springerbriefs in Applied Sciences and Technology Ser.
Format
Trade Paperback

Dimensions

Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Reviews
"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), "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)
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
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.
Synopsis
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.
LC Classification Number
Q342

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