基于网络关注度的旅游客流量预测研究  

Research on the Prediction of Tourist Flow Based on Network Attention

作　　者：王亮[1] Wang Liang(School of Finance&Economics,University of Sanya,Sanya 572022,China)

机构地区：[1]三亚学院财经学院,海南三亚572022

出　　处：《洛阳师范学院学报》2021年第7期24-29,共6页Journal of Luoyang Normal University

摘　　要：基于网络关注的旅游需求预测研究受到国内外学者广泛关注。用网络搜索指数的CLSI合成法和K-L距离合成法合成百度指数数据,引入ARMA模型,并比较了两者在旅游客流量预测能力上的差异。研究结果表明:CLSI指数合成法、K-L距离合成法有助于提高旅游客流量预测的准确性,前者的预测准确性高于后者。研究结果有助于旅游景区管理人员或相关部门对旅游客流的预测、管理。At present,the research on tourism demand prediction based on network attention has been widely concerned by scholars at home and abroad.In this paper,CLSI synthesis method and the K-L distance synthesis method are used to synthesize the Baidu index data which is introduced into the ARMA model,and their prediction ability of tourist flow is compared.The results show that both CLSI index synthesis method and K-L distance synthesis method can help improve the accuracy of tourist flow prediction,while the former is more accurate than the latter in accuracy.The research results are helpful for the management and related departments to forecast and manage the tourist flow.

关 键 词：旅游客流量 CLSI合成法 K-L距离合成法 百度指数 网络关注度 

分 类 号：F590[经济管理—旅游管理]