基于组合模型的陕西省旅游市场需求预测

Forecasting of tourism demands of Shaanxi Province based on combined model

为提高旅游需求预测的精度,提出一种基于BP神经网络和ARIMA组合模型的游客量预测方法,该方法能够同时考虑旅游统计数据的线性和非线性规律.以陕西省接待入境游客人数为例,采用组合模型进行了综合分析与预测,预测结果表明组合预测模型相对于单一的预测方法具有更高的精度,在旅游预测中是可行的、有效的.

In order to improve the precision of tourism demand forecasting, a combined forecasting model based on BP neural network and ARIMA model is proposed, where the linear and nonlinear relations are correctly modeled in the suggested method. The combined model is applied to the forecasting of overseas tourist to Shaanxi Province, and the variation in overseas tourist to Shaanxi Province is also analyzed. The result shows that the forecasting value of overseas tourist to Shaanxi Province based on the combined model has higher precision than monomial forecasting method, the combined model is feasible and effective in the forecasting of overseas tourist.