A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality of the fuzzy system design process. In previous works we have...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Apolloni, Javier, Kavka, Carlos, Roggero, Patricia
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2005
Materias:
Ciencias Informáticas
recurrent fuzzy systems
fuzzy control
voronoi diagrams
prior knowledge insertion
Algorithms
Robotics
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22940
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22940
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
recurrent fuzzy systems
fuzzy control
voronoi diagrams
prior knowledge insertion
Algorithms
Robotics
spellingShingle Ciencias Informáticas
recurrent fuzzy systems
fuzzy control
voronoi diagrams
prior knowledge insertion
Algorithms
Robotics
Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
topic_facet Ciencias Informáticas
recurrent fuzzy systems
fuzzy control
voronoi diagrams
prior knowledge insertion
Algorithms
Robotics
description A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality of the fuzzy system design process. In previous works we have introduced the RFV model, a representation for recurrent fuzzy controllers based on Voronoi diagrams that can represent fuzzy systems with synergistic rules, ful lling the completeness property and providing a simple way to introduce prior knowledge. In this work we present our current approach in the study of the inclusion of prior knowledge in the context of the RFV model
format Objeto de conferencia
Objeto de conferencia
author Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
author_facet Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
author_sort Apolloni, Javier
title A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
title_short A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
title_full A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
title_fullStr A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
title_full_unstemmed A study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
title_sort study of prior knowledge insertion in evolutionary fuzzy recurrent controllers design
publishDate 2005
url http://sedici.unlp.edu.ar/handle/10915/22940
work_keys_str_mv AT apollonijavier astudyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
AT kavkacarlos astudyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
AT roggeropatricia astudyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
AT apollonijavier studyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
AT kavkacarlos studyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
AT roggeropatricia studyofpriorknowledgeinsertioninevolutionaryfuzzyrecurrentcontrollersdesign
bdutipo_str Repositorios
_version_ 1764820467923812352

Ejemplares similares