An exploratory analysis of pedestrian accidents patterns in Lisbon

Detalhes bibliográficos
Autor(a) principal: Santo, Francisco José Monteiro do Espírito
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/134444
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling An exploratory analysis of pedestrian accidents patterns in LisbonPedestrian AccidentsLisbonK-MeansK-MedoidsClusterProject Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceMobility is one of the pillars of Smart Cities, being one of the most important issues for the development and growth of a city. Nowadays, with the massive flow of populations to large urban centers, mobility and its dangers require special attention. The number of pedestrian accidents has been increasing over the past few years, and it is important to understand what causes and factors contribute to them. The main objective of this work is to identify and classify the pedestrian accidents in the city of Lisbon and segment the accident patterns based on the application of clustering methods. The data used in this work was provided by Lisboa Aberta. The work begins with a literature review about the causes of pedestrian accidents previously identified and the reference of clustering methods used in similar studies. Then, a deep dive will be made of the data provided by Lisboa Aberta, selecting the most relevant variables used for the Cluster analysis. The Cluster analysis will be done using the K-Means and KMedoids methods. At the end of the work, the results of both methods will be compared, where the winning method will be chosen and the conclusions of which are the determining patterns in pedestrian accidents in the city of Lisbon will be presented.Neto, Miguel de Castro Simões FerreiraSarmento, Pedro Alexandre ReisRUNSanto, Francisco José Monteiro do Espírito2022-03-14T16:34:51Z2022-01-282022-01-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/134444TID:202962474enginfo: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:RCAAP2024-05-22T18:00:08Zoai:run.unl.pt:10362/134444Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:31:02.740997Repositórios 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 An exploratory analysis of pedestrian accidents patterns in Lisbon
title An exploratory analysis of pedestrian accidents patterns in Lisbon
spellingShingle An exploratory analysis of pedestrian accidents patterns in Lisbon
Santo, Francisco José Monteiro do Espírito
Pedestrian Accidents
Lisbon
K-Means
K-Medoids
Cluster
title_short An exploratory analysis of pedestrian accidents patterns in Lisbon
title_full An exploratory analysis of pedestrian accidents patterns in Lisbon
title_fullStr An exploratory analysis of pedestrian accidents patterns in Lisbon
title_full_unstemmed An exploratory analysis of pedestrian accidents patterns in Lisbon
title_sort An exploratory analysis of pedestrian accidents patterns in Lisbon
author Santo, Francisco José Monteiro do Espírito
author_facet Santo, Francisco José Monteiro do Espírito
author_role author
dc.contributor.none.fl_str_mv Neto, Miguel de Castro Simões Ferreira
Sarmento, Pedro Alexandre Reis
RUN
dc.contributor.author.fl_str_mv Santo, Francisco José Monteiro do Espírito
dc.subject.por.fl_str_mv Pedestrian Accidents
Lisbon
K-Means
K-Medoids
Cluster
topic Pedestrian Accidents
Lisbon
K-Means
K-Medoids
Cluster
description Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2022
dc.date.none.fl_str_mv 2022-03-14T16:34:51Z
2022-01-28
2022-01-28T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/134444
TID:202962474
url http://hdl.handle.net/10362/134444
identifier_str_mv TID:202962474
dc.language.iso.fl_str_mv eng
language eng
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.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
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repository.mail.fl_str_mv info@rcaap.pt
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