عنوان

Accuracy Improvements in Linguistic Fuzzy Modeling

9783540370581

9783642057038

b406950

Accuracy Improvements in Linguistic Fuzzy Modeling

[Book]

edited by Jorge Casillas, Oscar Cordón, Francisco Herrera, Luis Magdalena.

Berlin, Heidelberg :

Imprint: Springer,

2003.

Studies in Fuzziness and Soft Computing,

129

1434-9922 ;

Overview -- Accuracy Improvements Constrained by Interpretability Criteria -- Extending the Modeling Process to Improve the Accuracy -- Extending the Modeling Structure to Improve the Accuracy.

0

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.

9783642057038

Springer eBooks

Artificial intelligence.

Computer science.

Economics.

Engineering.

Operations research.

Physics.

Translators (Computer programs).

Casillas, Jorge.

Cordón, Oscar.

Herrera, Francisco.

Magdalena, Luis.

SpringerLink (Online service)

20190301073200.0

[Book]

Y