基于支持向量回归的机场旅客吞吐量预测

Predicting the Airport Passenger Throughput Based ona 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。

On the basis of analyzing the deficiency of predicating throughput both inward and outward,with the existing method,and in an application of the 'support vector regression method',which is formulated on the principle of minimizing a structural risk,a model to predicate passenger's throughput of an airport is established.With a comparison of the actual data to the result of the BP neural network, it is proved that using the support vector regression method to predicate the passengers throughput of an airport is workable,with a comparable precision.