摘要
旅游业是当今世界上发展最为迅速的产业,对其做出较为准确的预测,将有利于一国或一地区对其旅游发展做出合理规划以及对旅游资源进行优化配置,同时也有利于旅游企业制定出全面的战略计划。文中基于厦门市旅游业有关数据,在打破以时间序列态势为研究方法的指数平滑法的顺势推演预测思路的基础上,综合考虑影响旅游需求的主要因素,采用自学习能力较强的BP神经网络来预测旅游人数,力求寻找出合理的需求预测模型,从而为该地区的旅游规划提供一些参考依据。
Presently tourism is the fastest-growing industriy in the world.Making more accurate prediction will be good for a country or a region to make reasonable planning of tourism development and optimize the tourism resource configuration. Besides this will be good for travel companies to develop a comprehensive strategic plan.This paper is based on the data of the Xiamen city tourism,breaking the exponential smoothing prediction method which is the time series trend as research conveniently deduction.This paper considers the main travel demand factors,adopts BP neural network having the strong ability of self-learning to predict the number of tourist,tries to find out the reasonable demand forecasting model,and provide some reference basis for the regional tourism planning.
出处
《物流工程与管理》
2014年第3期171-172,170,共3页
Logistics Engineering and Management
关键词
旅游业
需求模型
BP神经网络
tourism
industry demand model
BP neural network
