Artificial Neural Networks can be a great help in port planning activity. Bad planning might lead to an incorrect use of the available resources and means. This research is focused on neural networks' behavior analysis within the port planning process, in the context of containers terminals, more precisely to study the possible traffic growth and the requirements in terms of equipment and installations. The traffic levels in these terminals and the minimum necessary investment can be thus evaluated with no need or with just a very low new investment. The methodology shows the fundamentals of the Artificial Neural Networks application and the considered sequence to develop the container port terminals planning, supported by the MATLAB code tools. The article reaches finally the conclusion that both the tool and the proposed methodology can be considered as acceptable to perform this kind of planning forecasts and to be used in the future. The results seem to show that the ANN can be used to model port planning issues linked to container terminals, based on historical data series.
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