Book Review: "Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases" by Oscar Cordon, Francisco Herrera, Frank Hoffmann and Luis Magdalena; World Scientific, Singapore,…

By Oscar Cordón, Francisco Herrera, Frank Hoffmann, L. Magdalena. Fuzzy Sets Syst., 2004

453 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting (2010, background): “Usually, they use complex rule generation mechanisms such as neural networks [32] or genetic algorithms [11].”
An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges (2012, background): “Consequently, to increase the accuracy of linguistic fuzzy systems two main processes have been introduced, a tuning process that aims to modify the membership function of the linguistic variables to obtain a better representation of the data and a rule selection process to optimize the rule base [2”
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design (2004, methodology): “In machine learning, GAs have been successfully applied to the learning of neural networks [9], [10] and fuzzy systems [ 11 ], [12].”
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? (2019, background): “Specifically, the intrinsic understandability, comprehensibility, and explainability associated with FRBSs, and the potential of EAs as the optimization technique for improving FRBSs, leads to what is known as evolutionary fuzzy systems (EFSs) [21].”