{"id":2699,"date":"2019-10-14T16:04:22","date_gmt":"2019-10-14T19:04:22","guid":{"rendered":"https:\/\/eic.cefet-rj.br\/ppcic\/?p=2699"},"modified":"2025-09-03T18:53:32","modified_gmt":"2025-09-03T21:53:32","slug":"defesa-de-dissertacao-13-11-2019-leonardo-da-silva-moreira","status":"publish","type":"post","link":"https:\/\/eic.cefet-rj.br\/ppcic\/defesa-de-dissertacao-13-11-2019-leonardo-da-silva-moreira\/","title":{"rendered":"Defesa de disserta\u00e7\u00e3o (13\/11\/2019): Leonardo da Silva Moreira"},"content":{"rendered":"

Discente:<\/strong> Leonardo da Silva Moreira<\/p>\n

T\u00edtulo<\/strong>: Evaluation of Data Preprocessing Methods for Predicting Brazilian Flight Delays<\/p>\n

Orientador<\/strong>: Jorge de Abreu Soares (orientador), Eduardo Soares Ogasawara (co-orientador)<\/p>\n

Banca<\/strong>: Jorge de Abreu Soares (presidente), Eduardo Soares Ogasawara (CEFET\/RJ), Eduardo Bezerra da Silva (CEFET\/RJ), Leonardo Gresta Paulino Murta (IC\/UFF)<\/p>\n

Dia\/Hora<\/strong>: 13 de novembro de 2019 \/14 horas<\/p>\n

Sala<\/strong>: E-522<\/p>\n

Resumo<\/strong>:<\/p>\n

Em 2016, as receitas do setor de servi\u00e7os a\u00e9reos do Brasil alcan\u00e7aram um recorde hist\u00f3rico de receita de R$35,59 bilh\u00f5es, transportando 109,6 milh\u00f5es de passageiros de acordo com levantamento da Ag\u00eancia Nacional de Avia\u00e7\u00e3o Civil (ANAC). Considerando esse cen\u00e1rio, atrasos nos voos causam v\u00e1rios inconvenientes para as companhias a\u00e9reas, aeroportos e passageiros como ocorreram entre 2009 e 2015, onde cerca de 22% dos voos dom\u00e9sticos realizados no Brasil sofreram atrasos superiores a 15 minutos. A previs\u00e3o desses atrasos \u00e9 fundamental para mitigar sua ocorr\u00eancia e otimizar o processo de tomada de decis\u00e3o de um sistema de transporte a\u00e9reo. Particularmente, companhias a\u00e9reas, aeroportos e usu\u00e1rios podem estar mais interessados em saber quando \u00e9 prov\u00e1vel que ocorram atrasos do que a previs\u00e3o precisa de quando n\u00e3o ocorrer\u00e3o. Neste contexto, esta pesquisa apresenta uma avalia\u00e7\u00e3o experimental de m\u00e9todos de pr\u00e9-processamento de dados para modelos de classifica\u00e7\u00e3o de aprendizado de m\u00e1quina para a predi\u00e7\u00e3o dos atrasos a\u00e9reos, de forma a identificar quais m\u00e9todos e combina\u00e7\u00f5es destes m\u00e9todos podem auxiliar na melhora da predi\u00e7\u00e3o e dos resultados do classificador sob uma distribui\u00e7\u00e3o desequilibrada de classes de atraso. Para isto a metodologia utilizada inclui a integra\u00e7\u00e3o de dados a\u00e9reos e meteorol\u00f3gicos, etapas de pr\u00e9-processamento [limpeza, transforma\u00e7\u00e3o, redu\u00e7\u00e3o] e finalmente a compara\u00e7\u00e3o da predi\u00e7\u00e3o de dados a partir destes diferentes m\u00e9todos de pr\u00e9-processamento. Particularmente, esta pesquisa contribui com a an\u00e1lise de um espectro de m\u00e9todos de pr\u00e9-processamento de dados quando comparado \u00e0 revis\u00e3o bibliogr\u00e1fica, focando especialmente a distribui\u00e7\u00e3o das classes de atraso. Incluem-se entre os objetivos deste trabalho a verifica\u00e7\u00e3o mais detalhada em rela\u00e7\u00e3o aos atributos do classificador,a normaliza\u00e7\u00e3o e discretiza\u00e7\u00e3o, principalmente no que diz respeito \u00e0 faixa de par\u00e2metros do filtro.<\/p>\n

\"\"<\/a><\/div>\n
Disserta\u00e7\u00e3o <\/strong>\"\"<\/a><\/div>\n

 [:en]Student:<\/strong> Leonardo da Silva Moreira<\/p>\n

Title<\/strong>: Evaluation of Data Preprocessing Methods for Predicting Brazilian Flight Delays<\/p>\n

Advisors<\/strong>: Jorge de Abreu Soares (advisor), Eduardo Soares Ogasawara (co-advisor)<\/p>\n

Committee<\/strong>: Jorge de Abreu Soares (president), Eduardo Soares Ogasawara (CEFET\/RJ), Eduardo Bezerra da Silva (CEFET\/RJ), Leonardo Gresta Paulino Murta (IC\/UFF)<\/p>\n

Day\/Time<\/strong>: November 13, 2019 \/ 14h<\/p>\n

Room<\/strong>: E-522<\/p>\n

Abstract<\/strong>:<\/p>\n

In 2016, revenues from Brazil’s air services sector reached record revenue of $ R$ 35.59$ billion, transporting 109.6 million passengers, according to a survey by the National Civil Aviation Agency (ANAC). Considering this scenario, delays in flights cause several inconveniences to airlines, airports, and passengers as they occurred between 2009 and 2015, where about 22% of domestic flights made in Brazil were delayed for more than 15 minutes. Predicting these delays is critical to mitigate their occurrence and optimize the decision-making process of an air transport system. In particular, airlines, airports, and users may be more interested in knowing when delays are likely to occur than the forecast needs to know when they will not occur. In this context, this research presents an experimental evaluation of data preprocessing methods for machine learning classification models for the prediction of flight delays, in order to identify which methods and combinations of these methods can help improve prediction and results of the classifier under an unbalanced distribution of delay classes. For this, the methodology used includes the integration of aerial and meteorological data, pre-processing steps [cleaning, transformation, reduction] and finally the comparison of data prediction from these different pre-processing methods. In particular, this research contributes to the analysis of a spectrum of data preprocessing methods when compared to the bibliographic review, especially focusing on the distribution of delay classes. Among the objectives of this work are the more detailed verification in relation to the attributes of the classifier, the normalization, and discretization, mainly with respect to the range of parameters of the filter.<\/p>\n

\"\"<\/a><\/div>\n
Dissertation <\/strong>\"\"<\/a><\/div>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Discente: Leonardo da Silva Moreira T\u00edtulo: Evaluation of Data Preprocessing Methods for Predicting Brazilian Flight Delays Orientador: Jorge de Abreu Soares (orientador), Eduardo Soares Ogasawara (co-orientador) Banca: Jorge de Abreu Soares (presidente), Eduardo Soares Ogasawara (CEFET\/RJ), Eduardo Bezerra da Silva (CEFET\/RJ), Leonardo Gresta Paulino Murta (IC\/UFF) Dia\/Hora: 13 de novembro de 2019 \/14 horas Sala: […]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[14,33],"tags":[],"class_list":["post-2699","post","type-post","status-publish","format-standard","hentry","category-defesas","category-noticias-pt"],"_links":{"self":[{"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/posts\/2699","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/comments?post=2699"}],"version-history":[{"count":11,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/posts\/2699\/revisions"}],"predecessor-version":[{"id":2708,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/posts\/2699\/revisions\/2708"}],"wp:attachment":[{"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/media?parent=2699"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/categories?post=2699"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/ppcic\/wp-json\/wp\/v2\/tags?post=2699"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}