摘要
为提高旅游大数据利用效率,在研究了大数据五维范式基础上,对旅游大数据中天气、温度、周末和公共假期与目的地游客到达量和目的地搜索热度的相关性进行了研究,并探索了目的地实际到达人数与其搜索热度之间的Granger因果关系。通过仿真分析,该方法能够有效分析各变量之间的关系。仿真结果进一步验证了该方法的有效性及实用性。
In order to improve the utilization efficiency of tourism big data,this paper studied the correlation between weather,temperature,weekends and public holidays with the number of tourists arriving at the destination and the search heat of destination based on the study of the five dimensional paradigm of big data,and explored the Granger causality between the number of actual arrivals and the search heat.Through simulation analysis,this method could effectively analyze the relationship between the variables.The simulation results further verified the effectiveness and practicability of the proposed method.
作者
刘燕
LIU Yan(Xi′an Eurasian University, Xi′an 710065, China)
出处
《林业调查规划》
2022年第3期181-184,共4页
Forest Inventory and Planning
基金
西安欧亚学院校级科研基金项目(2020XJSK16).
