基于BP神经网络的港口货物吞吐量预测

Port Cargo Throughput Forecast Based on BP Neural Network

港口货物吞吐量的预测对于港口的建设和规划有着极其重要的意义。本文将BP神经网络理论引入港口货物吞吐量的预测中,建立以港口货物吞吐量影响因素作为输入神经元,港口货物吞吐量作为输出神经元的三层BP神经网络模型,并对南京港货物吞吐量进行预测,得到较好的预测结果。

Forecast of port throughput is very important for port construction and layout. This thesis introduces the theories of BP Neural Network into the field of cargo throughput forecast, and sets up a three-layer neural network model with the factor influencing the cargo throughput as the input artificial neuron, and the cargo throughput as the output artificial neuron. The model achieves promptly the accurate and satisfactory results in the Nanjing cargo throughput forecast.