Refinement of a fuzzy control rule set.

Antonio González; Raúl Pérez

Mathware and Soft Computing (1998)

  • Volume: 5, Issue: 2-3, page 175-187
  • ISSN: 1134-5632

Abstract

top
Fuzzy logic controller performance depends on the fuzzy control rule set. This set can be obtained either by an expert or from a learning algorithm through a set of examples. Recently, we have developed SLAVE an inductive learning algorithm capable of identifying fuzzy systems. The refinement of the rules proposed by SLAVE (or by an expert) can be very important in order to improve the accuracy of the model and in order to simplify the description of the system. The refinement algorithm is based on an heuristic process of generalization, specification, addition and elimination of rules.

How to cite

top

González, Antonio, and Pérez, Raúl. "Refinement of a fuzzy control rule set.." Mathware and Soft Computing 5.2-3 (1998): 175-187. <http://eudml.org/doc/39133>.

@article{González1998,
abstract = {Fuzzy logic controller performance depends on the fuzzy control rule set. This set can be obtained either by an expert or from a learning algorithm through a set of examples. Recently, we have developed SLAVE an inductive learning algorithm capable of identifying fuzzy systems. The refinement of the rules proposed by SLAVE (or by an expert) can be very important in order to improve the accuracy of the model and in order to simplify the description of the system. The refinement algorithm is based on an heuristic process of generalization, specification, addition and elimination of rules.},
author = {González, Antonio, Pérez, Raúl},
journal = {Mathware and Soft Computing},
keywords = {Algoritmos de aprendizaje; Control lógico; Lógica difusa; Optimización; Inteligencia artificial; fuzzy logic controller; theory refinement; fuzzy logic; machine learning; system modeling},
language = {eng},
number = {2-3},
pages = {175-187},
title = {Refinement of a fuzzy control rule set.},
url = {http://eudml.org/doc/39133},
volume = {5},
year = {1998},
}

TY - JOUR
AU - González, Antonio
AU - Pérez, Raúl
TI - Refinement of a fuzzy control rule set.
JO - Mathware and Soft Computing
PY - 1998
VL - 5
IS - 2-3
SP - 175
EP - 187
AB - Fuzzy logic controller performance depends on the fuzzy control rule set. This set can be obtained either by an expert or from a learning algorithm through a set of examples. Recently, we have developed SLAVE an inductive learning algorithm capable of identifying fuzzy systems. The refinement of the rules proposed by SLAVE (or by an expert) can be very important in order to improve the accuracy of the model and in order to simplify the description of the system. The refinement algorithm is based on an heuristic process of generalization, specification, addition and elimination of rules.
LA - eng
KW - Algoritmos de aprendizaje; Control lógico; Lógica difusa; Optimización; Inteligencia artificial; fuzzy logic controller; theory refinement; fuzzy logic; machine learning; system modeling
UR - http://eudml.org/doc/39133
ER -

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.