二手船价格是买卖二手船决策过程中非常关键的因素。为了准确地估算二手船价格,利用BP神经网络的高度非线性运算能力以及通过学习样本数据即可对事物复杂内在规律进行精确计算的特点,将BP神经网络应用于二手船价格的估算。利用从克拉克松获取的2009年到2012年120个灵便型干散货船交易数据,建立了基于船龄、船舶载重吨(DWT)、新造船价格和一年期期租费率的BP神经网络模型,网络输出结果与二手船实际交易价格的相对误差率在10%以内。 Used boat prices are a crucial factor in the decision-making process of buying and selling used boats. In order to accurately estimate the price of second-hand ships, the BP neural network is applied to the estimation of the price of second-hand ships by using the highly nonlinear computing ability of BP neural network and the accurate calculation of complicated internal laws by learning sample data. Using BP data from 120 shipments of handymax dry bulk vessels from Clarke, 2009 to 2012, BP neural networks based on age of ships, DWT, newbuilding costs and one-year rates were set up Model, the network output and second-hand ship the actual transaction price relative error rate of less than 10%.