Article ID Journal Published Year Pages File Type
4961691 Procedia Computer Science 2016 6 Pages PDF
Abstract

Maritime transport rates are very important for planning economic strategies. Various methods have been applied to seaborne trade forecasting. This study presents a genetic algorithm based trained recurrent fuzzy neural network for long term dry cargo freight rates forecasting. The empirical results show that proposed work has better accuracy than the other approaches which have used the same data set.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
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