Milenković, Miloš

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Container flow forecasting through neural networks based on metaheuristics

Milenković, Miloš; Milosavljević, Nataša S.; Bojović, Nebojša; Susana, Vall

(Springer, 2019)

TY  - JOUR
AU  - Milenković, Miloš
AU  - Milosavljević, Nataša S.
AU  - Bojović, Nebojša
AU  - Susana, Vall
PY  - 2019
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/6829
AB  - In this paper we propose a fuzzy neural network prediction approach based on metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for selection between two different heuristics for developing neural network architecture, simulated annealing and genetic algorithm, respectively. These non-parametric models are compared with traditional parametric ARIMA technique. Time series composed from monthly container traffic observations for Port of Barcelona are used for model developing and testing. Models are compared based on the most important criteria for performance evaluation and for each of the data sets (total container traffic, loaded, unloaded, transit and empty) the appropriate model is selected.
PB  - Springer
T2  - Operational research
T1  - Container flow forecasting through neural networks based on metaheuristics
EP  - 997
SP  - 965
VL  - 21
DO  - 10.1007/s12351-019-00477-1
ER  - 
@article{
author = "Milenković, Miloš and Milosavljević, Nataša S. and Bojović, Nebojša and Susana, Vall",
year = "2019",
abstract = "In this paper we propose a fuzzy neural network prediction approach based on metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for selection between two different heuristics for developing neural network architecture, simulated annealing and genetic algorithm, respectively. These non-parametric models are compared with traditional parametric ARIMA technique. Time series composed from monthly container traffic observations for Port of Barcelona are used for model developing and testing. Models are compared based on the most important criteria for performance evaluation and for each of the data sets (total container traffic, loaded, unloaded, transit and empty) the appropriate model is selected.",
publisher = "Springer",
journal = "Operational research",
title = "Container flow forecasting through neural networks based on metaheuristics",
pages = "997-965",
volume = "21",
doi = "10.1007/s12351-019-00477-1"
}
Milenković, M., Milosavljević, N. S., Bojović, N.,& Susana, V.. (2019). Container flow forecasting through neural networks based on metaheuristics. in Operational research
Springer., 21, 965-997.
https://doi.org/10.1007/s12351-019-00477-1
Milenković M, Milosavljević NS, Bojović N, Susana V. Container flow forecasting through neural networks based on metaheuristics. in Operational research. 2019;21:965-997.
doi:10.1007/s12351-019-00477-1 .
Milenković, Miloš, Milosavljević, Nataša S., Bojović, Nebojša, Susana, Vall, "Container flow forecasting through neural networks based on metaheuristics" in Operational research, 21 (2019):965-997,
https://doi.org/10.1007/s12351-019-00477-1 . .
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