基于EMD的景区客流波动特征及其组合预测——以黄山风景区为例

旅游地的发展演化过程研究大多采用Bulter 的生命周期理论路径, 少有文献从波动的视角理解和分析旅游地的发展演化过程。本文以黄山风景区为例, 采用经验模态分解方法(EMD)尝试从波动的视角分析景区客流波动特征, 并利用波动性特征对其发展进行组合预测(经验模态分解方法和最小二乘支持向量机方法的组合)。研究结果表明:黄山景区客流波动呈现出多种形态, 在增长趋势的基础上叠加了季节性波动、景区旅游周期波动和景区经济周期波动。其与最小二乘支持向量机组合预测模型能够对景区客流进行有效预测, 并且运算速度快, 预测精度有所提高;与生命周期曲线相比较更加直观、微观、准确, 并且能够进行较为准确的客流预报, 有助于景区规划管理和战略决策。

Research on Fluctuation Characteristics and Combined Forecasting of Tourist Arrivals in Huangshan Scenic Areas

The research on dynamic evolution of tourist destination has been confined to the path of Bulter’s destination lifecycle model so that other research perspectives including fluctuation model have been neglected.Taking Huangshan Scenic Areas as a case study,this paper analyzes fluctuation characteristics of tourist arrivals by Empirical Mode Decomposition(EMD),and employs a combined forecasting model to predict tourist arrivals based on EMD and LS-SVM(Least Squares Support Vector Machines).The results show that the fluctuationof tourist arrials in Huangshan Scenic Areas present such patterns as continuously increasing trend,seasonal fluctuation,tourism cycles and economic cycles,and the combined forecasting model can predict tourist arrivals more rapidly and more accurately.All in all,EMD from fluctuation perspective can disclose dynamic evolution more directly,deeply and accurately,and combined with LS-SVM it can accurately predict tourist arrivals,which is conductive to planning management and strategic decision of scenic areas.