Prior knowledge 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...

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Detalles Bibliográficos
Autores principales: Apolloni, Javier, Kavka, Carlos, Roggero, Patricia
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2005
Materias:
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prior Knowledge
Evolutionary Fuzzy Recurrent
Controllers Design
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21160
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21160
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
ARTIFICIAL INTELLIGENCE
Prior Knowledge
Evolutionary Fuzzy Recurrent
Controllers Design
spellingShingle Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prior Knowledge
Evolutionary Fuzzy Recurrent
Controllers Design
Apolloni, Javier
Kavka, Carlos
Roggero, Patricia
Prior knowledge in evolutionary fuzzy recurrent controllers design
topic_facet Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Prior Knowledge
Evolutionary Fuzzy Recurrent
Controllers Design
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 Prior knowledge in evolutionary fuzzy recurrent controllers design
title_short Prior knowledge in evolutionary fuzzy recurrent controllers design
title_full Prior knowledge in evolutionary fuzzy recurrent controllers design
title_fullStr Prior knowledge in evolutionary fuzzy recurrent controllers design
title_full_unstemmed Prior knowledge in evolutionary fuzzy recurrent controllers design
title_sort prior knowledge in evolutionary fuzzy recurrent controllers design
publishDate 2005
url http://sedici.unlp.edu.ar/handle/10915/21160
work_keys_str_mv AT apollonijavier priorknowledgeinevolutionaryfuzzyrecurrentcontrollersdesign
AT kavkacarlos priorknowledgeinevolutionaryfuzzyrecurrentcontrollersdesign
AT roggeropatricia priorknowledgeinevolutionaryfuzzyrecurrentcontrollersdesign
bdutipo_str Repositorios
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