Information Sciences
Volume 136, Issue 1-4, August 2001
Recent Advances in Genetic Fuzzy Systems

O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena (Eds.)

Table of Contents

Recent advances in genetic fuzzy systems
O. Cordón, F. Herrera, F. Hoffmann and L. Magdalena
1-5

Genetic programming for model selection of TSK-fuzzy systems
Frank Hoffmann and Oliver Nelles
7-28

Hierarchical genetic fuzzy systems
Myriam Regattieri Delgado, Fernando Von Zuben and Fernando Gomide
29-52

Fuzzy modeling using genetic algorithms with fuzzy entropy as conciseness measure
T. Suzuki, T. Kodama, T. Furuhashi and H. Tsutsui
53-67

Optimizing lattice-based associative memory networks by evolutionary algorithms
Ingo Renners and Adolf Grauel
69-84

A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base
O. Cordón, F. Herrera, L. Magdalena and P. Villar
85-107

Three-objective genetics-based machine learning for linguistic rule extraction
Hisao Ishibuchi, Tomoharu Nakashima and Tadahiko Murata
109-133

Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems
J. Casillas, O. Cordón, M.J. Del Jesus and F. Herrera
135-157

An experimental study about the search mechanism in the SLAVE learning algorithm: Hill-climbing methods versus genetic algorithms
Antonio González and Raúl Pérez
159-174

Combining GP operators with SA search to evolve fuzzy rule based classifiers
Luciano Sánchez, Inés Couso and J.A. Corrales
175-191

Approximative fuzzy rules approaches for classification with hybrid-GA techniques
Antonio F. Gómez-Skarmeta, Mercedes Valdés, Fernando Jiménez and Javier G. Marín-Blázquez
193-214

Learning fuzzy classifier systems for multi-agent coordination
Andrea Bonarini and Vito Trianni
215-239