基于EEMD-GA-BP的组合客流预测算法研究

Combined passenger flow prediction algorithm based on EEMD-GA-BP

摘要: 以高速铁路泰安站到达客流为研究对象，从客流数据的时频特性角度分析客流的特征，并结合经验模态分解法的时频分析优势以及遗传算法优化的神经网络的拟合能力，探索可行组合预测算法，以泰安站到达客流数据为例进行了实例分析，比较不同的IMF分量重构方法并确定了较优方案。

Abstract: This article analyzed the passenger flow time and frequency characteristic of Tai’an Station, explored a feasible combination forecasting algorithm combining with EEMD and GA-BP Algorithms, taken the travelers of Tai’an Station as example to analyze and compare different reconstruction methods of IMFs, determine the optimal one.