Fonte: Neurocomputing. Unidade: EESC
Assuntos: ENGENHARIA DE TRÁFEGO (OTIMIZAÇÃO), SISTEMAS DE CONTROLE, TEMPO-REAL, ALGORITMOS GENÉTICOS
ABNT
DEZANI, Henrique et al. Optimizing urban traffic flow using genetic algorithm with Petri net analysis as fitness function. Neurocomputing, v. 124, n. Ja 2014, p. 162-167, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2013.07.015. Acesso em: 30 set. 2024.APA
Dezani, H., Bassi, R. D. S., Marranghello, N., Gomes, L., Damiani, F., & Silva, I. N. da. (2014). Optimizing urban traffic flow using genetic algorithm with Petri net analysis as fitness function. Neurocomputing, 124( Ja 2014), 162-167. doi:10.1016/j.neucom.2013.07.015NLM
Dezani H, Bassi RDS, Marranghello N, Gomes L, Damiani F, Silva IN da. Optimizing urban traffic flow using genetic algorithm with Petri net analysis as fitness function [Internet]. Neurocomputing. 2014 ; 124( Ja 2014): 162-167.[citado 2024 set. 30 ] Available from: https://doi.org/10.1016/j.neucom.2013.07.015Vancouver
Dezani H, Bassi RDS, Marranghello N, Gomes L, Damiani F, Silva IN da. Optimizing urban traffic flow using genetic algorithm with Petri net analysis as fitness function [Internet]. Neurocomputing. 2014 ; 124( Ja 2014): 162-167.[citado 2024 set. 30 ] Available from: https://doi.org/10.1016/j.neucom.2013.07.015