基于GEP的高速公路通行费预测方法研究

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-17 Cooperative journals: 《计算机应用研究》

刘宁 黄樟灿 谈庆

Abstract： The prediction of the future income of highway toll has great guiding significance for the management and construction planning. However, the change of toll income is influenced by many factors. It has strong nonlinearity and complexity. The traditional prediction model cannot accurately express the development law of the toll income. In this paper, a highway toll prediction model based on gene expression programming algorithm (GEP) is established. The GEP algorithm is used to establish a complex functional relationship between current income and historical data, which accurately characterize the development rule of toll income over time. In addition, an effective correction model is proposed for the influence of toll reduction policies during holidays. Finally, this paper collects the historical data on the toll revenue of 12 companies such as shanghai-hangzhou-ningbo Expressway Co. , Ltd. Compared with traditional ARIMA and neural network prediction model, and the results fully verify the effectiveness and accuracy of the proposed algorithm.

 Hits 1687  Downloads 936  Comment