Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location

This paper is republished with permission of the International Institute of Acoustics and Vibration. It was originally published in the Proceedings of the 29th International Congress on Sound and Vibration, Prague, July 9-13, 2023

Detalhes bibliográficos
Autores: Anahi, Martin, Pita Lozano, Antonio, Navarro, Juan Miguel
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2023
País:España
Recursos:Universitat Oberta de Catalunya (UOC)
Repositório:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/152275
Acesso em linha:http://hdl.handle.net/10609/152275
Access Level:Acceso aberto
Palavra-chave:sensitivity analysis
environmental noise assessment
wireless acoustic sensor network
neural network
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spelling Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a LocationAnahi, MartinPita Lozano, AntonioNavarro, Juan Miguelsensitivity analysisenvironmental noise assessmentwireless acoustic sensor networkneural networkThis paper is republished with permission of the International Institute of Acoustics and Vibration. It was originally published in the Proceedings of the 29th International Congress on Sound and Vibration, Prague, July 9-13, 2023To manage noise pollution, cities use monitoring systems over wireless acoustic sensor networks. These networks are mainly composed of fixed-location sound pressure level sensors deployed in outdoor sites of the city for long-term monitoring. However, due to high economic and human resource costs, it is not feasible to deploy fixed metering stations on every street in a city. Therefore, these continuous measurements are usually complemented with short-term measurements at different selected locations, which are carried out by acoustic sensors mounted on vehicles or at street level. In this research, the sensitivity of artificial neural networks for estimation of the long-term environmental acoustic pattern of a location based on the information collected during a short time period is analyzed. An evaluation has been carried out through a comparison of eight artificial neural network architectures using real data from the acoustic sensor network of Barcelona, Spain, showing that precision and recall performance appears to be more strongly associated with environmental patterns rather than the considered architecture.The International Institute of Acoustics and Vibration (IIAV)202520252023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10609/152275reponame:O2, repositorio institucional de la UOCinstname:Universitat Oberta de Catalunya (UOC)Inglés29th International Congress on Sound and Vibration (ICSV29)info:eu-repo/grantAgreement/AEI/2020/PID2020-112827GB-I00Copyright© (2023) by The International Institute of Acoustics and Vibration (IIAV)info:eu-repo/semantics/openAccessoai:openaccess.uoc.edu:10609/1522752026-05-28T12:42:01Z
dc.title.none.fl_str_mv Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
title Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
spellingShingle Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
Anahi, Martin
sensitivity analysis
environmental noise assessment
wireless acoustic sensor network
neural network
title_short Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
title_full Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
title_fullStr Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
title_full_unstemmed Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
title_sort Sensitivity Analysis and Architecture Selection of Artificial Neural Networks for Estimation of the Environmental Acoustic Pattern of a Location
dc.creator.none.fl_str_mv Anahi, Martin
Pita Lozano, Antonio
Navarro, Juan Miguel
author Anahi, Martin
author_facet Anahi, Martin
Pita Lozano, Antonio
Navarro, Juan Miguel
author_role author
author2 Pita Lozano, Antonio
Navarro, Juan Miguel
author2_role author
author
dc.subject.none.fl_str_mv sensitivity analysis
environmental noise assessment
wireless acoustic sensor network
neural network
topic sensitivity analysis
environmental noise assessment
wireless acoustic sensor network
neural network
description This paper is republished with permission of the International Institute of Acoustics and Vibration. It was originally published in the Proceedings of the 29th International Congress on Sound and Vibration, Prague, July 9-13, 2023
publishDate 2023
dc.date.none.fl_str_mv 2023
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10609/152275
url http://hdl.handle.net/10609/152275
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv 29th International Congress on Sound and Vibration (ICSV29)
info:eu-repo/grantAgreement/AEI/2020/PID2020-112827GB-I00
dc.rights.none.fl_str_mv Copyright© (2023) by The International Institute of Acoustics and Vibration (IIAV)
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright© (2023) by The International Institute of Acoustics and Vibration (IIAV)
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv The International Institute of Acoustics and Vibration (IIAV)
publisher.none.fl_str_mv The International Institute of Acoustics and Vibration (IIAV)
dc.source.none.fl_str_mv reponame:O2, repositorio institucional de la UOC
instname:Universitat Oberta de Catalunya (UOC)
instname_str Universitat Oberta de Catalunya (UOC)
reponame_str O2, repositorio institucional de la UOC
collection O2, repositorio institucional de la UOC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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