Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods

Bibliographic Details
Main Author: Stepnicka, M.
Publication Date: 2011
Other Authors: Peralta Donate, Juan, Cortez, Paulo, Vavricková, L., Gutierrez Sanchez, German
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/14840
Summary: Accurate time series forecasting are important for displaying the manner in which the past contin- ues to affect the future and for planning our day to day activities. In recent years, a large litera- ture has evolved on the use of computational in- telligence in many forecasting applications. In this paper, several computational intelligence techniques (genetic algorithms, neural networks, support vec- tor machine, fuzzy rules) are combined in a distinct way to forecast a set of referenced time series. Fore- casting performance is compared to the a standard and method frequently used in practice.
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spelling Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methodsTime seriesComputational intelligenceNeural networksSupport vector machineFuzzy rulesGenetic algorithmScience & TechnologyAccurate time series forecasting are important for displaying the manner in which the past contin- ues to affect the future and for planning our day to day activities. In recent years, a large litera- ture has evolved on the use of computational in- telligence in many forecasting applications. In this paper, several computational intelligence techniques (genetic algorithms, neural networks, support vec- tor machine, fuzzy rules) are combined in a distinct way to forecast a set of referenced time series. Fore- casting performance is compared to the a standard and method frequently used in practice.Project DAR 1M0572 of the MŠMT ČR.Atlantis PressUniversidade do MinhoStepnicka, M.Peralta Donate, JuanCortez, PauloVavricková, L.Gutierrez Sanchez, German2011-072011-07-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/14840eng978-90-78677-00-01951-6851http://www.atlantis-press.com/info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T05:40:21Zoai:repositorium.sdum.uminho.pt:1822/14840Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:26:11.634706Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
title Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
spellingShingle Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
Stepnicka, M.
Time series
Computational intelligence
Neural networks
Support vector machine
Fuzzy rules
Genetic algorithm
Science & Technology
title_short Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
title_full Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
title_fullStr Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
title_full_unstemmed Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
title_sort Forecasting seasonal time series with computational intelligence: contribution of a combination of distinct methods
author Stepnicka, M.
author_facet Stepnicka, M.
Peralta Donate, Juan
Cortez, Paulo
Vavricková, L.
Gutierrez Sanchez, German
author_role author
author2 Peralta Donate, Juan
Cortez, Paulo
Vavricková, L.
Gutierrez Sanchez, German
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Stepnicka, M.
Peralta Donate, Juan
Cortez, Paulo
Vavricková, L.
Gutierrez Sanchez, German
dc.subject.por.fl_str_mv Time series
Computational intelligence
Neural networks
Support vector machine
Fuzzy rules
Genetic algorithm
Science & Technology
topic Time series
Computational intelligence
Neural networks
Support vector machine
Fuzzy rules
Genetic algorithm
Science & Technology
description Accurate time series forecasting are important for displaying the manner in which the past contin- ues to affect the future and for planning our day to day activities. In recent years, a large litera- ture has evolved on the use of computational in- telligence in many forecasting applications. In this paper, several computational intelligence techniques (genetic algorithms, neural networks, support vec- tor machine, fuzzy rules) are combined in a distinct way to forecast a set of referenced time series. Fore- casting performance is compared to the a standard and method frequently used in practice.
publishDate 2011
dc.date.none.fl_str_mv 2011-07
2011-07-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/14840
url http://hdl.handle.net/1822/14840
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-90-78677-00-0
1951-6851
http://www.atlantis-press.com/
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 Atlantis Press
publisher.none.fl_str_mv Atlantis Press
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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