%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16c/2018/12.27.17.58
%2 sid.inpe.br/mtc-m16c/2018/12.27.17.58.01
%@issn 2179-4847
%T Generating artificial data for bus travel time predictions
%D 2018
%A Ribeiro, Leandro S.,
%A Faleiros, Thiago P.,
%A Holanda, Maristela,
%@affiliation Universidade de Brasília (UnB)
%@affiliation Universidade de Brasília (UnB)
%@affiliation Universidade de Brasília (UnB)
%E Vinhas, Lúbia (INPE),
%E Campelo, Claudio (UFCG),
%B Simpósio Brasileiro de Geoinformática, 19 (GEOINFO)
%C Campina Grande
%8 05-07 dez. 2018
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 13-24
%X This paper proposes a simulator capable of quickly generating a large amount of data that may be used to train bus travel time predictive algorithms in an urban transport network. To validate the proposal, a case study was car- ried out on a bus line in the city of Bras ́ılia/DF, Brazil. In the case study, the Simulator generated data for several scenarios that differ in distinct levels of variability and these data were used to evaluate the performance of a K-Nearest Neighbor predictor in each of the scenarios.
%@language pt
%3 p2.pdf