Optimizing propagation models on railway communications using genetic algorithms

Detalhes bibliográficos
Autor(a) principal: Beire, Ana Rita
Data de Publicação: 2014
Outros Autores: Pinheiro Pita, Helder Jorge, Cota, Nuno
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/12296
Resumo: Although the Okumura-Hata prediction model has been a widely used model to estimate radio network coverage, its application in railways environment requires calibration. The objective of this work is to present Genetic Algorithms as a solution in optimizing propagation models, proving that it can be used for optimizing the Okumura-Hata model on railway communications in order to improve its prediction of radio coverage. Several tests were carried out using different conditions allowing to establish the conditions that maximize the gain of the algorithm for this particular problem. The algorithm was applied to training samples and the resulting parameters were applied to different scenarios, showing improvements in the prediction results.
id RCAP_0c2ff0eca38e4412d2d63a2f881554d7
oai_identifier_str oai:repositorio.ipl.pt:10400.21/12296
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Optimizing propagation models on railway communications using genetic algorithmsOptimizationPropagation modelOkumura-hataGenetic algorithmsRailway communicationsAlthough the Okumura-Hata prediction model has been a widely used model to estimate radio network coverage, its application in railways environment requires calibration. The objective of this work is to present Genetic Algorithms as a solution in optimizing propagation models, proving that it can be used for optimizing the Okumura-Hata model on railway communications in order to improve its prediction of radio coverage. Several tests were carried out using different conditions allowing to establish the conditions that maximize the gain of the algorithm for this particular problem. The algorithm was applied to training samples and the resulting parameters were applied to different scenarios, showing improvements in the prediction results.ElsevierRCIPLBeire, Ana RitaPinheiro Pita, Helder JorgeCota, Nuno2020-10-27T11:28:03Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/12296engBEIRE, Ana Rita; PITA, Helder; COTA, Nuno – Optimizing propagation models on railway communications using genetic algorithms. Procedia Technology. ISSN 2212-0173. Vol. 17 (2014), pp. 50-572212-017310.1016/j.protcy.2014.10.215info: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:RCAAP2023-08-03T10:04:55Zoai:repositorio.ipl.pt:10400.21/12296Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:20:24.742759Repositório 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 Optimizing propagation models on railway communications using genetic algorithms
title Optimizing propagation models on railway communications using genetic algorithms
spellingShingle Optimizing propagation models on railway communications using genetic algorithms
Beire, Ana Rita
Optimization
Propagation model
Okumura-hata
Genetic algorithms
Railway communications
title_short Optimizing propagation models on railway communications using genetic algorithms
title_full Optimizing propagation models on railway communications using genetic algorithms
title_fullStr Optimizing propagation models on railway communications using genetic algorithms
title_full_unstemmed Optimizing propagation models on railway communications using genetic algorithms
title_sort Optimizing propagation models on railway communications using genetic algorithms
author Beire, Ana Rita
author_facet Beire, Ana Rita
Pinheiro Pita, Helder Jorge
Cota, Nuno
author_role author
author2 Pinheiro Pita, Helder Jorge
Cota, Nuno
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Beire, Ana Rita
Pinheiro Pita, Helder Jorge
Cota, Nuno
dc.subject.por.fl_str_mv Optimization
Propagation model
Okumura-hata
Genetic algorithms
Railway communications
topic Optimization
Propagation model
Okumura-hata
Genetic algorithms
Railway communications
description Although the Okumura-Hata prediction model has been a widely used model to estimate radio network coverage, its application in railways environment requires calibration. The objective of this work is to present Genetic Algorithms as a solution in optimizing propagation models, proving that it can be used for optimizing the Okumura-Hata model on railway communications in order to improve its prediction of radio coverage. Several tests were carried out using different conditions allowing to establish the conditions that maximize the gain of the algorithm for this particular problem. The algorithm was applied to training samples and the resulting parameters were applied to different scenarios, showing improvements in the prediction results.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
2020-10-27T11:28:03Z
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/10400.21/12296
url http://hdl.handle.net/10400.21/12296
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv BEIRE, Ana Rita; PITA, Helder; COTA, Nuno – Optimizing propagation models on railway communications using genetic algorithms. Procedia Technology. ISSN 2212-0173. Vol. 17 (2014), pp. 50-57
2212-0173
10.1016/j.protcy.2014.10.215
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 Elsevier
publisher.none.fl_str_mv Elsevier
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
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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
repository.mail.fl_str_mv
_version_ 1799133473378664448