# Organization & Editorial Activities: Edited Books

Accuracy Improvements in Linguistic Fuzzy Modeling

J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.)

Table of Contents

Foreword

P. Bonissone

Preface

J. Casillas, O. Cordón, F. Herrera, L. Magdalena

## 1. OVERVIEW

Accuracy improvements to find the balance interpretability-accuracy in linguistic fuzzy modeling: an overview*J. Casillas, O. Cordón, F. Herrera, L. Magdalena*

p. 3

## 2. ACCURACY IMPROVEMENTS CONSTRAINED BY INTERPRETABILITY CRITERIA

COR methodology: a simple way to obtain linguistic fuzzy models with good interpretability and accuracy*J. Casillas, O. Cordón, F. Herrera*

p. 27

Constrained optimization of genetic fuzzy systems*F. Cheong, R. Lai*

p. 46

Trade-off between the number of fuzzy rules and their classification performance*H. Ishibuchi, T. Yamamoto*

p. 72

Generating distinguishable, complete, consistent and compact fuzzy systems using evolutionary algorithms*Y. Jin*

p. 100

Fuzzy CoCo: balancing accuracy and interpretability of fuzzy models by means of coevolution*C.A. Peña-Reyes, M. Sipper*

p. 119

On the achievement of both accurate and interpretable fuzzy systems using data-driven design processes*J. Valente de Oliveira, P. Fazendeiro*

p. 147

## 3. EXTENDING THE MODELING PROCESS TO IMPROVE THE ACCURACY

Linguistic hedges and fuzzy rule based systems*C.-Y. Chen, B.-D. Liu*

p. 165

Automatic construction of fuzzy rule-based fuzzy systems: A trade-off between complexity and accuracy maintaining interpretability*H. Pomares, I. Rojas, J. González*

p. 193

Using individually tested rules for the databased generation of interpretable rule bases with high accuracy*T. Slawinski, P. Krause, H. Kiendl*

p. 220

## 4. EXTENDING THE MODEL STRUCTURE TO IMPROVE THE ACCURACY

A description of several characteristics for improving the accuracy and interpretability of the fuzzy rule learning algorithms*E. Aguirre, A. González, R. Pérez*

p. 249

An iterative learning methodology to design hierarchical systems of linguistic rules for linguistic modeling*R. Alcalá, O. Cordón, F. Herrera, I. Zwir*

p. 277

Learning default fuzzy rules with general and punctual exceptions*P. Carmona, J.L. Castro, J.J. Castro-Schez, M. Laguia*

p. 302

Integration of fuzzy knowledge*T.-P. Hong, C.-H. Wang, S.-S. Tseng*

p. 338

Tuning fuzzy partitions or assigning weights to fuzzy rules: which is better?*L. Sánchez, J. Otero*

p. 366