@inproceedings{847f2f4f41ac45558f9419e159128baf,
title = "Short-term traffic congestion forecasting using hybrid metaheuristics and rule-based methods: A comparative study",
abstract = "In this paper, a comparative study between a hybrid technique that combines a Genetic Algorithm with a Cross Entropy method to optimize Fuzzy Rule-Based Systems, and literature techniques is presented. These techniques are applied to traffic congestion datasets in order to determine their performance in this area. Different types of datasets have been chosen. The used time horizons are 5, 15 and 30min. Results show that the hybrid technique improves those results obtained by the techniques of the state of the art. In this way, the performed experimentation shows the competitiveness of the proposal in this area of application.",
keywords = "Classification, Cross entropy, Fuzzy rule-based systems, Genetic algorithms, Hybrid optimization, Intelligent transportation systems, Machine learning",
author = "Pedro Lopez-Garcia and Eneko Osaba and Enrique Onieva and Masegosa, \{Antonio D.\} and Asier Perallos",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016 ; Conference date: 14-09-2016 Through 17-09-2016",
year = "2016",
doi = "10.1007/978-3-319-44636-3\_27",
language = "English",
isbn = "9783319446356",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "290--299",
editor = "Edurne Barrenechea and Alicia Troncoso and G{\'a}mez, \{Jos{\'e} A.\} and Oscar Luaces and H{\'e}ctor Quinti{\'a}n and Emilio Corchado and Mikel Galar",
booktitle = "Advances in Artificial Intelligence - 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, Proceedings",
address = "Germany",
}
