Accuracy improvements in linguistic fuzzy modeling
type: Item
instance of: scholarly article
title: Accuracy improvements in linguistic fuzzy modeling
zbMATH Open document ID: 1040.68116
published in: Studies in Fuzziness and Soft Computing
publication date: 2003-06-24T00:00:00Z
review text: The main purpose of the present paper is to provide a comprehensive yet detailed overview of the approaches based on hybrid Soft Computing (SC) systems developed as flexible computing tools to improve the accuracy in linguistic fuzzy systems. The intrinsic need for trading off interpretability and accuracy in the use of SC systems, in particular of fuzzy (logic) systems, is focused in the papers enclosed in the book on improving accuracy while preserving interpretability within fuzzy linguistic modelling. To obtain high degrees of interpretability (i.e. capability to express the behaviour of the real systems in an understandable way) and accuracy (viz, capability to faithfully represent the real systems) is a contradictory purpose and, in practice, one of two properties prevails over the other. While linguistic fuzzy modelling (mainly developed by linguistic fuzzy systems) is centered on interpretability, precise fuzzy modelling (mainly developed by Takagi-Sugeno-Kang fuzzy systems) is concentrated on accuracy. From this perspective, the role played by this book is to present in detail a state-of-the-art on the recent proposals that attempt to obtain linguistic fuzzy models with a good, reliable interpretability-accuracy trade-off inclined however towards improving their accuracy feature. The present book is organized in four main sections comprising (a total of) 15 chapters. Section 1 (Overview) and its only enclosed Chapter 1 (J. Casillas, O. Ordón, F. Herrera and L. Magdalena: ``Accuracy improvements to find the balance interpretability-accuracy in linguistic fuzzy modelling: an overview'') offers an enlightening survey of the various accuracy improvement mechanisms existing in the recent literature. Section 2 (Accuracy Improvements constrained by Interpretability Criteria) collects a set of contributions focusing on the use of different accuracy developments performed under some constraints that avoid an excessive interpretability loss; restrictions such as rigi…
Mathematics Subject Classification ID: 68T37
Mathematics Subject Classification ID: 68T35
Mathematics Subject Classification ID: 68-06
Mathematics Subject Classification ID: 00B15
Mathematics Subject Classification ID: 68T50
Mathematics Subject Classification ID: 93C42
Mathematics Subject Classification ID: 68T27
Mathematics Subject Classification ID: 68T30
Mathematics Subject Classification ID: 03B52
zbMATH DE Number: 1934211
zbMATH Keywords: hybrid soft computing modelling
zbMATH Keywords: interpretability-accuracy trade-off
zbMATH Keywords: fuzzy rule-based systems
zbMATH Keywords: evolutionary algorithm in fuzzy systems
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1934211