基于变异系数加权的旅游需求组合预测模型

A Combined Forecasting Model of Tourism Demand Based on Variation Coefficient Weighted

随着第三产业的快速发展,旅游业在推动经济增长中起着越来越重要的作用。本文利用变异系数法对单一的预测模型加权,建立了地区旅游需求量的组合预测模型。通过与GM(1,1)模型、线性趋势外推法和指数趋势外推法的预测误差进行比较,发现组合预测模型在对江西省旅游总收入的预测中精度更高,而线性趋势外推法对江西接待旅游总人次的预测中误差最小。文章最后利用实证得出的最优模型,对江西省未来五年的旅游需求做了预测。

With the rapid development of the tertiary industry, tourism plays an increasingly important role in promoting economic growth. In this paper, the variance coefficient method is used to weight the single prediction model, and the combined forecasting model of regional tourism demand is established. By comparing with the GM（1,1） model,the linear trend extrapolation method and the extrapolation method of the exponential trend extrapolation method, it is found that the combined forecasting model is more accurate in predicting the total tourism income of Jiangxi Province, and the linear trend extrapolation. The paper makes a prediction on the forecast of the total number of people in Jiangxi Province, and finally uses the optimal model of empirical evidence to forecast the tourism demand of Jiangxi Province in the next five years.