人工智能方法在旅游预测中的应用及评析

对旅游需求预测的研究始于20世纪60年代，绝大多数研究成果出现于80年代以后。而对此类文献进行整理和研究的成果相对较少，且有明显的缺陷：一是研究深度不够，仅仅是对近期论文的简单罗列；二是由于受研究时间的局限性，未能涉及最新的研究方法。为此，系统地论述诸如粗糙集理论、遗传算法、时间序列方法等，并通过比较得出：人工智能方法在旅游预测方面的应用尽管取得了较好的效果，但也有其自身的缺陷，在以后的研究中应发挥各种分析方法的优点，根据实际分析对象的具体情况选择合适的分析方法，这样才能收到事半功倍的效果。

A Literature Review and Application about Artificial Intelligence in Tourism Demand Forecasting

Researches on tourism demand forecasting started from the 1960s, and the majority of research results appeared after the 1980s. But there are few reviews on those literatures and the reviews also have distinct shortcomings. Firstly, the depth of the reviews are not enough, just simply listed the recent issues. Secondly, due to the limitation of the time, those reviews failed to involve the newest analysis methods. This paper discuses the application of artificial intelligence in tourism demand forecasting and its merits and defects. By comparing with traditional tourism forecasting methods like econometric models and time- series, it shows that the application of artificial intelligence in tourism demand forecasting is effective, but also has limitations. Therefore, we should make full use of advantages of analysis methods, and choose appropriate methods according as specific analysis object, and then we can get twice the result with half the effort