基于支持向量回归的旅客吞吐量预测研究

Predicting the Airport Passenger Throughput Based on a Support Vector Regression Model

在分析现有机场旅客吞吐量预测方法不足的基础上,利用基于结构风险最小化原则的支持向量回归方法,建立了机场旅客吞吐量预测模型。通过实际数据的检验及与BP神经网络等方法的预测结果相比较,证明应用支持向量回归方法对机场旅客吞吐量进行预测具备可行性,同时具有较高的预测精度。

This paper analyzes the deficiency of current methods of predicting the airport passenger throughput and uses the support vector regression method to construct a model to predict the airport passenger throughput. Through the test of actual data and the contrast with the prediction of other methods, people can conclude that using the support vector regression method to predict the airport passenger throughput is workable and comparatively precise.