Max-Min fuzzy neural networks for solving relational equations

The Relational Equations approach is one of the most usual ones for describing (Fuzzy) Systems and in most cases, it is the final expression for other descriptions. This is why the identification of Relational Equations from a set of examples has received considerable atention in the specialized lit...

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Detalhes bibliográficos
Autores: Blanco Morón, Armando, Delgado Calvo-Flores, Miguel, Requena Ramos, Ignacio
Tipo de documento: artigo
Data de publicação:1994
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2099/2461
Acesso em linha:https://hdl.handle.net/2099/2461
Access Level:Acceso aberto
Palavra-chave:Fuzzy relational equations
Max-min neural networks
Sistemes autoorganitzatius
Aprenentatge automàtic
Intel·ligència artificial
Bases de dades relacionals
Classificació AMS::68 Computer science::68T Artificial intelligence
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oai_identifier_str oai:upcommons.upc.edu:2099/2461
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repository_id_str
spelling Max-Min fuzzy neural networks for solving relational equationsBlanco Morón, ArmandoDelgado Calvo-Flores, MiguelRequena Ramos, IgnacioFuzzy relational equationsMax-min neural networksSistemes autoorganitzatiusAprenentatge automàticIntel·ligència artificialBases de dades relacionalsClassificació AMS::68 Computer science::68T Artificial intelligenceThe Relational Equations approach is one of the most usual ones for describing (Fuzzy) Systems and in most cases, it is the final expression for other descriptions. This is why the identification of Relational Equations from a set of examples has received considerable atention in the specialized literature. This paper is devoted to this topic, more specifically to the topic of max-min neural networks for identification. Three methods of "learning" Fuzzy Systems are developed by combining the most desirable properties of two existing ones: Sayto-Mukaidono's technique and the so called "smoothed derivative" technique.Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica19941994-01-0120072007-03-05journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2099/2461reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099/24612026-05-27T15:37:01Z
dc.title.none.fl_str_mv Max-Min fuzzy neural networks for solving relational equations
title Max-Min fuzzy neural networks for solving relational equations
spellingShingle Max-Min fuzzy neural networks for solving relational equations
Blanco Morón, Armando
Fuzzy relational equations
Max-min neural networks
Sistemes autoorganitzatius
Aprenentatge automàtic
Intel·ligència artificial
Bases de dades relacionals
Classificació AMS::68 Computer science::68T Artificial intelligence
title_short Max-Min fuzzy neural networks for solving relational equations
title_full Max-Min fuzzy neural networks for solving relational equations
title_fullStr Max-Min fuzzy neural networks for solving relational equations
title_full_unstemmed Max-Min fuzzy neural networks for solving relational equations
title_sort Max-Min fuzzy neural networks for solving relational equations
dc.creator.none.fl_str_mv Blanco Morón, Armando
Delgado Calvo-Flores, Miguel
Requena Ramos, Ignacio
author Blanco Morón, Armando
author_facet Blanco Morón, Armando
Delgado Calvo-Flores, Miguel
Requena Ramos, Ignacio
author_role author
author2 Delgado Calvo-Flores, Miguel
Requena Ramos, Ignacio
author2_role author
author
dc.subject.none.fl_str_mv Fuzzy relational equations
Max-min neural networks
Sistemes autoorganitzatius
Aprenentatge automàtic
Intel·ligència artificial
Bases de dades relacionals
Classificació AMS::68 Computer science::68T Artificial intelligence
topic Fuzzy relational equations
Max-min neural networks
Sistemes autoorganitzatius
Aprenentatge automàtic
Intel·ligència artificial
Bases de dades relacionals
Classificació AMS::68 Computer science::68T Artificial intelligence
description The Relational Equations approach is one of the most usual ones for describing (Fuzzy) Systems and in most cases, it is the final expression for other descriptions. This is why the identification of Relational Equations from a set of examples has received considerable atention in the specialized literature. This paper is devoted to this topic, more specifically to the topic of max-min neural networks for identification. Three methods of "learning" Fuzzy Systems are developed by combining the most desirable properties of two existing ones: Sayto-Mukaidono's technique and the so called "smoothed derivative" technique.
publishDate 1994
dc.date.none.fl_str_mv 1994
1994-01-01
2007
2007-03-05
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099/2461
url https://hdl.handle.net/2099/2461
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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