Inteligência computacional aplicada ao futebol americano
Ano de defesa: | 2018 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Rio de Janeiro
Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11422/11567 |
Resumo: | This work presents the application of computational intelligence models to support amateur level american footbal teams. Two models were developed, with the goal of supporting coaches and athletes, using data from different sources. One specialist neural network ensemble was trained, using data from a high level american team, in order to extract what game characteristics affect playcall, for a professional team. The ensemble could identify a relevant set of attributes among the ones analyzed. Using data collected for amateur level players, a ranking algorithm was developed. This model was used to rank athletes on a weekly training camp opened to all players. The model was also use privately for an amateur team from Rio de Janeiro, to rank their players during the season. |