基于灰色理论与支持向量机组合的旅游数据预测模型研究

The Forecasting Model Research of Tourism Data Based on Grey Theory and Support Vector Machine

旅游数据分析对于促进我国各地区的旅游经济发展和文化交流都有着重要的意义。由于旅游数据的＂小样本、贫信息、不确定＂特性,旅游市场可以看作是一个巨大的灰色系统。但是由于传统灰色预测方法存在一些理论缺陷,无法准确的预测旅游收入等数据,为了提高旅游数据的预测精度,为政府和旅游部门决策提供支持,将灰色模型与支持向量机模型通过最优权组合,将组合预测模型应用于旅游数据的预测,并以泰安市旅游数据为例,得到较好的预测结果。

It＇s important for the development of tourism economy and cultural exchange that analyzing data of tourism. Because of the tourism data has ＂small sample, poor information, and uncertain＂ features, tourism market can be seen as a huge gray system. But due to the traditional forecast method of gray theory has some defects, This paper combined the grey model and support vector machine （SVM） mode by the optimal weight. Combination forecasting model was applied to tourism data prediction and obtain a better prediction results.