Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports

Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with exces...

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Bibliographic Details
Published in:Discrete dynamics in nature and society 2017-01, Vol.2017 (2017), p.1-15
Main Authors: Gökkuş, Ümit, Aydin, Metin Mutlu, Yıldırım, Mehmet Sinan
Format: Article
Language:English
Subjects:
Artificial neural networks
Comparative analysis
Containers
Developing countries
Economic models
Exports
Feasibility studies
Forecasting
GDP
Genetic algorithms
Gross Domestic Product
Harbors
International trade
LDCs
Mathematical models
Neural networks
Population growth
Ports
Short term
Soft computing
Statistical methods
Traffic
Traffic engineering
Traffic estimation
Traffic models
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Summary:Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey.
ISSN:1026-0226
1607-887X
DOI:10.1155/2017/2984853