摘要
20世纪90年代之前,对旅游需求预测一般采用传统的定量分析方法,而近20年来,诸如粗糙集、遗传算法、模糊时间序列、灰色理论、神经网络模型、支持向量机等人工智能方法也被引入到旅游需求预测的研究之中。然而,国内外学者尚未对人工智能方法在旅游需求预测中的应用进行系统的整理与论述。为此,本文简要介绍了人工智能在旅游预测中的应用,并与传统的计量方法、时间序列方法进行了比较。同时,简略评述了其优缺点和发展趋势。
Prior to 1990s, traditional quantitative analysis method was generally applied in tourism forecast for demand. But in the past twenty years, such artificial intelligence methods as rough sets, genetic algorithms, fuzzy time series, grey theory, artificial neural networks and vector machines have been introduced into the study of tourism forecast. However, scholars both at home and abroad have not had any systematic comment on it. Accordingly, the paper tries to give a brief introduction to the application of artificial intelligence method in tourism forecast and compare it with the traditional measuring method and time series method. Meanwhile, its strong and weak points as well as developing trend are briefly commented.
出处
《旅游学刊》
CSSCI
北大核心
2008年第9期17-22,共6页
Tourism Tribune
关键词
人工智能方法
旅游预测
应用
评析
artificial intelligence method
tourism forecast
application
comment and analysis
