Interpretability Issues in Fuzzy Modeling

Jorge Casillas

ISBN 10: 3642057020 / ISBN 13: 9783642057021

Published by Springer Berlin Heidelberg Dez 2010, 2010

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -Fuzzy modeling has become one of the most productive and successful results of fuzzy logic. Among others, it has been applied to knowledge discovery, automatic classification, long-term prediction, or medical and engineering analysis. The research developed in the topic during the last two decades has been mainly focused on exploiting the fuzzy model flexibility to obtain the highest accuracy. This approach usually sets aside the interpretability of the obtained models. However, we should remember the initial philosophy of fuzzy sets theory directed to serve the bridge between the human understanding and the machine processing. In this challenge, the ability of fuzzy models to express the behavior of the real system in a comprehensible manner acquires a great importance. This book collects the works of a group of experts in the field that advocate the interpretability improvements as a mechanism to obtain well balanced fuzzy models. 660 pp. Englisch.

Seller Inventory # 9783642057021

Bibliographic Details

• Title: Interpretability Issues in Fuzzy Modeling
• Publisher: Springer Berlin Heidelberg Dez 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 3642057020
• ISBN 13: 9783642057021
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 36D millimeters 235 millimeters width by 155 millimeters height by 36 millimeters depth
• Weight: 984 grams

About this title

Synopsis

Fuzzy modeling has become one of the most productive and successful results of fuzzy logic. Among others, it has been applied to knowledge discovery, automatic classification, long-term prediction, or medical and engineering analysis. The research developed in the topic during the last two decades has been mainly focused on exploiting the fuzzy model flexibility to obtain the highest accuracy. This approach usually sets aside the interpretability of the obtained models. However, we should remember the initial philosophy of fuzzy sets theory directed to serve the bridge between the human understanding and the machine processing. In this challenge, the ability of fuzzy models to express the behavior of the real system in a comprehensible manner acquires a great importance. This book collects the works of a group of experts in the field that advocate the interpretability improvements as a mechanism to obtain well balanced fuzzy models.