微型电脑应用

旅游景点人流量高精度预测一直属于旅游产业中必不可少、但有待优化的问题,旅游景点人流预测属于分析旅游需求的关键。由此,构建了一个基于层次分析法的旅游景点人流预测模型,首先通过基于动态聚类的游客信息分类方法,获取旅游地某个景点的指定游客信息样本;然后针对此样本,使用基于层次分析法的组合预测模型,实现旅游景点人流预测。研究结果验证:所构建模型可实现旅游景点人流高精度预测。且和同类模型相比,该模型在预测旅游景点人流量时,对游客信息的查全率与查准率均存在一定优势,可实现全面的游客信息提取,且相关信息管理人员对该模型的应用反馈极高,应用价值较好。

High-precision prediction of tourist attraction flow has always been an essential and yet to be optimized problem in the tourism industry, and the prediction of tourist attraction flow is the key to analyze the tourism demand. Therefore, this paper constructs a forecast model of tourist attraction flow based on AHP. Firstly, through the classification method of tourist information based on dynamic clustering, it obtains the designated tourist information sample of a certain tourist attraction. Then, according to this sample, it uses the combination forecast model based on AHP to realize the prediction of tourist attraction flow. The results show that the model can achieve high-precision prediction of tourist attraction flow. Compared with the similar model, the model has certain advantages in the recall and precision of tourist information when predicting the tourist flow of tourist attractions, which can achieve a comprehensive extraction of tourist information, and the application feedback of relevant information management personnel to the model is very high, and the application value is good.