A multicriteria genetic tuning for fuzzy logic controllers.

Rafael Alcalá; Jorge Casillas; Juan Luis Castro; Antonio González; Francisco Herrera

Mathware and Soft Computing (2001)

  • Volume: 8, Issue: 2, page 179-201
  • ISSN: 1134-5632

Abstract

top
This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria -which enlarges the solution search space-, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning strategies considering different multicriteria approaches have been developed and tested in a real-world problem for fuzzy control of HVAC Systems.

How to cite

top

Alcalá, Rafael, et al. "A multicriteria genetic tuning for fuzzy logic controllers.." Mathware and Soft Computing 8.2 (2001): 179-201. <http://eudml.org/doc/39221>.

@article{Alcalá2001,
abstract = {This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria -which enlarges the solution search space-, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning strategies considering different multicriteria approaches have been developed and tested in a real-world problem for fuzzy control of HVAC Systems.},
author = {Alcalá, Rafael, Casillas, Jorge, Castro, Juan Luis, González, Antonio, Herrera, Francisco},
journal = {Mathware and Soft Computing},
keywords = {Controladores; Control difuso; Multicriterios; genetic algorithms; multicriteria complex problems},
language = {eng},
number = {2},
pages = {179-201},
title = {A multicriteria genetic tuning for fuzzy logic controllers.},
url = {http://eudml.org/doc/39221},
volume = {8},
year = {2001},
}

TY - JOUR
AU - Alcalá, Rafael
AU - Casillas, Jorge
AU - Castro, Juan Luis
AU - González, Antonio
AU - Herrera, Francisco
TI - A multicriteria genetic tuning for fuzzy logic controllers.
JO - Mathware and Soft Computing
PY - 2001
VL - 8
IS - 2
SP - 179
EP - 201
AB - This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria -which enlarges the solution search space-, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning strategies considering different multicriteria approaches have been developed and tested in a real-world problem for fuzzy control of HVAC Systems.
LA - eng
KW - Controladores; Control difuso; Multicriterios; genetic algorithms; multicriteria complex problems
UR - http://eudml.org/doc/39221
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.