灰色支持向量机在机场吞吐量预测中的应用

在分析传统预测方法不足的基础上,利用灰色支持向量机组合分析模型,以实际值与灰色模型预测值的比值序列作为支持向量机模型的输入,选取径向基函数为核函数,并通过交叉验证法选取最优参数,利用支持向量机模型分析预测比值序列,最后通过灰色模型还原为货邮吞吐量的预测值.以上海机场货邮吞吐量为例,对灰色支持向量机模型进行了实证分析,并与灰色模型、支持向量机模型进行了对比.

Grey Support Vector Machine Combination Model Applied in Predicting the Throughput of Airport

The deficiency of current methods for predicting the airport total cargo was analysed and the grey support vector machine combination model was introduced to predict the airport total cargo.The ratio sequence of the actual values to the results predicted by the gray model was regarded as an input of the support vector machine model,and the radial basis function was selected as a kernel function.By use of cross validation method the optimal parameter was searched.The support vector machine model was then applied to predict the real ratio sequence,and finally the result was restored to the value of the airport total cargo by using again the gray model.The total cargo of Shanghai airport was taken as an example to illustrate the feasibility of the model,and its results were compared with those predicted by the gray model and the support vector machine model.