基于ARIMA-SVR的福建省入境游客人数预测

Prediction of the Number of Inbound Tourists in Fujian Province Based on ARIMA-SVR

精确预测旅游人数能帮助旅游业高质量发展。根据旅游人数是时序性和非线性的特征,具有时变性、非线性和非平稳性特征。文章提出基于差分自回归移动平均(ARIMA)和支持向量机回归(SVR)的混合预测模型,利用福建省入境游客历史数据对模型进行验证。实验结果表明,基于ARIMA与SVR的混合模型预测精度高,更能准确描述旅游人数时间序列的复杂变化趋势。

Accurate prediction of the number of tourists can help the high-quality development of the tourism industry.Since the number of tourists is characterized by time series and non-linearness,this prediction has time-varying,non-linear and non-stationary characteristics.In this paper,a hybrid prediction model based on autoregressive integrated moving average(ARIMA)and support vector regression(SVR)is proposed,and the historical data of inbound tourists in Fujian Province are used to verify the model.The experimental results show that the hybrid model based on ARIMA and SVR has high prediction and can more accurately describe the complex changes of the time series of tourists.