The BDI Prediction Research Based On Adaptive Neural Network

Because the dry bulk shipping market is affected by many uncertain factors, the freight index of the market always fluctuates sharply, and the traditional forecasting methods are not suitable to its predication. This gives difficulty for the market participants to make decisions. This developing models to forecast the freight index through studying the internal laws and external influence factors, can provide a powerful tool for operators and investors to understand the market trend and avoid the price risk.First of all, this paper analyzes the structure and form of the dry bulk shipping market and indicates the assortment and features of the dry bulk shipping market. And then, conducts the research on the factor of freight index forecasting. Secondly, introduces the features of BDI forecasting and reasons to choose ANN and the weak point of ANN. Then pay an emphasis on the adjustment of the structure of BP-ANN. This paper innovate to the adaptive control of ANN structure in order to the convenience of BDI'forecasting. The trained model and the forecasted results are obtained through The Unscrambler X, it can select sudden factors. Finally, the numerical analysis shows that the adaptive control of ANN model has accuracy and can be used to predict the trend of the freight rates of the Baltic bulk carriers.