Dynamic aperiodic neural network for time series prediction

Detalhes bibliográficos
Autor(a) principal: Chiu-Che, Tseng
Data de Publicação: 2007
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/10013
Resumo: There are many things that humans find easy to do that computers are currently unable to do. Tasks such as visual pattern manipulating objects by touch, and navigating in a complex world are easy for humans. Yet, despite decades of research, we have no viable algorithms for performing these and other cognitive functions on a computer. In this study, we used a bio-inspired neural network called a KA­ set neural network to perform a time series predictive task. The results from our experiments showed that the predictive accuracy with this method was better in most markets than results obtained using a random walk method.
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spelling Dynamic aperiodic neural network for time series predictionKset neural networkTime seriesPredictionThere are many things that humans find easy to do that computers are currently unable to do. Tasks such as visual pattern manipulating objects by touch, and navigating in a complex world are easy for humans. Yet, despite decades of research, we have no viable algorithms for performing these and other cognitive functions on a computer. In this study, we used a bio-inspired neural network called a KA­ set neural network to perform a time series predictive task. The results from our experiments showed that the predictive accuracy with this method was better in most markets than results obtained using a random walk method.Instituto Superior de Economia e GestãoRepositório da Universidade de LisboaChiu-Che, Tseng2015-11-03T11:38:40Z20072007-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/10013engChiu-Che, Tseng (2007). "Dynamic aperiodic neural network for time series prediction". Portuguese Journal of Management Studies, XII(2):99-114info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:40:24Zoai:www.repository.utl.pt:10400.5/10013Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:56:33.438472Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Dynamic aperiodic neural network for time series prediction
title Dynamic aperiodic neural network for time series prediction
spellingShingle Dynamic aperiodic neural network for time series prediction
Chiu-Che, Tseng
Kset neural network
Time series
Prediction
title_short Dynamic aperiodic neural network for time series prediction
title_full Dynamic aperiodic neural network for time series prediction
title_fullStr Dynamic aperiodic neural network for time series prediction
title_full_unstemmed Dynamic aperiodic neural network for time series prediction
title_sort Dynamic aperiodic neural network for time series prediction
author Chiu-Che, Tseng
author_facet Chiu-Che, Tseng
author_role author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Chiu-Che, Tseng
dc.subject.por.fl_str_mv Kset neural network
Time series
Prediction
topic Kset neural network
Time series
Prediction
description There are many things that humans find easy to do that computers are currently unable to do. Tasks such as visual pattern manipulating objects by touch, and navigating in a complex world are easy for humans. Yet, despite decades of research, we have no viable algorithms for performing these and other cognitive functions on a computer. In this study, we used a bio-inspired neural network called a KA­ set neural network to perform a time series predictive task. The results from our experiments showed that the predictive accuracy with this method was better in most markets than results obtained using a random walk method.
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-01-01T00:00:00Z
2015-11-03T11:38:40Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/10013
url http://hdl.handle.net/10400.5/10013
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Chiu-Che, Tseng (2007). "Dynamic aperiodic neural network for time series prediction". Portuguese Journal of Management Studies, XII(2):99-114
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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