Prediction for the Region Disposition of Panama Dry Bulk Fleet Management

Abstract

The region disposition prediction is important to the fleet management of shipping company to make effective decisions. To obtain the future marine environment, support vector machine (SVM) is used due to the advantage of prediction performance based on small samples. Since the incorrectly recorded data would affect the prediction performance of SVM obviously, K-nearest neighbors (KNN) is adopted to filter the input data in data processing. The prediction model based on KNN and SVM is validated by the data. The Baltic Freight Index (BPI index) of four routes and the decision-making of different companies was considered in prediction processing to improve the accuracy of our model. In the example calculation, results show that the proposed prediction model can increase the rental income of fleet effectively, and it would help the shipping company to make decisions of fleet management.

Keywords

• Region disposition of fleet management
• K-nearest neighbor
• support vector machine
• BPI index