机场旅客吞吐量的人工神经网络预测方法

利用人工神经网络对非线性系统的函数所具有的以任意精度逼近的良好特性 ,突破传统上基于统计学原理进行机场旅客吞吐量预测的限制 ,设计了具有成都双流国际机场特点的、低成本的机场旅客吞吐量的人工神经网络预测模型 ,经过 BP网络预测软件运行检验 ,并与该机场以前采用的定量预测方法的综合比较 ,证明在该机场应用 BP网络预测方法不仅可行 ,而且有更好的预测精度

Artificial Neural Networks Method for Predicting the Airport Passenger Throughput

Making use of the favorable specific property that ANN(the Artificial Neural Networks) may put forward the non-linear system with any precision, the author breaks through the restriction in the airport passenger throughput prediction based on the traditional statistics and designs a low-cost CDIA passenger throughput prediction model. Being tested by BP-ANN(one kind of ANN) prediction software, the BP-ANN predicting method has been testified to be workable and more accurate than those quantitative predicting methods used before in CDIA.