Accuracy Improvements in Linguistic Fuzzy Modeling

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Synopsis

Fuzzy modeling usually comes with two contradictory requirements: interpretability, which is the capability to express the real system behavior in a comprehensible way, and accuracy, which is the capability to faithfully represent the real system. In this framework, one of the most important areas is linguistic fuzzy modeling, where the legibility of the obtained model is the main objective. This task is usually developed by means of linguistic (Mamdani) fuzzy rule-based systems. An active research area is oriented towards the use of new techniques and structures to extend the classical, rigid linguistic fuzzy modeling with the main aim of increasing its precision degree. Traditionally, this accuracy improvement has been carried out without considering the corresponding interpretability loss. Currently, new trends have been proposed trying to preserve the linguistic fuzzy model description power during the optimization process. Written by leading experts in the field, this volume collects some representative researcher that pursue this approach.

Book details

Edition:
2003
Series:
Studies in Fuzziness and Soft Computing (Book 129)
Author:
Francisco Herrera Triguero, Luis Magdalena, Jorge Casillas, O. Cordón
ISBN:
9783540370581
Related ISBNs:
9783540029335
Publisher:
Springer Berlin Heidelberg
Pages:
N/A
Reading age:
Not specified
Includes images:
No
Date of addition:
2022-08-26
Usage restrictions:
Copyright
Copyright date:
2003
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Business and Finance, Computers and Internet, Mathematics and Statistics, Nonfiction, Technology