近些年，上海的都市旅游发展迅速，各大景区客流量也出现日益增多的情况，为了进一步了解上海景区在节假日和工作日等不同时段的客流变化特征，本项目通过上海市旅游局官方微信公众号“乐游上海”统计了2018年3月15日至2018年10月15日上海市35个3A级及以上景区每日10:00和15:00客流量，在此基础上，通过描述统计分析得出上海旅游景区每日15：00客流量普遍高于10:00客流量。通过K-means聚类分析发现几个热门景点占据了上海每日大部分客流量，而大部分3A及4A景区客流量仍处于较低水平。通过对不同类型的景区客流量进行时间序列分析，建立ARIMA模型，得出上海市3A及以上景区客流量存在不同的波动性，并且在时间上存在相互影响。本项目通过描述性统计分析，K-means聚类分析及时间序列建模的方法，图形与模型并存，直观科学地分析了客流量的分布情况并预测了景区客流量的未来趋势，希望能对上海旅游业发展提供帮助。
In recent years,
with the rapid development of urban tourism in Shanghai, the passenger flow of
major scenic spots is increasing day by day. In order to further understand the
changing characteristics of the passenger flow of Shanghai scenic spots in
different periods, such as holidays and working days, this program counts 35
scenic spots of 3A level and above in Shanghai from March 15, 2018 to October
15, 2018 through the official Wechat public number of Shanghai Tourism Bureau,
“Happy Tour Shanghai”. The daily passenger flow is 10:00 and 15:00. On the
basis, through descriptive statistical analysis, it is concluded that the daily
passenger flow at 15:00 is generally higher than that at 10:00 in Shanghai
tourist attraction. K-means cluster shows that several popular scenic spots
occupy most of the daily passenger flow in Shanghai, while most of the 3A and
4A scenic spots are still at a low level. Through time series analysis of
passenger flow in different scenic spots, ARIMA model is established. It is
concluded that there are different fluctuations of passenger flow in scenic
spots 3A and above in Shanghai, and there are mutual influences in time.
Through descriptive statistical analysis, K-means clustering analysis and time
series modeling, graphics and models coexists; this project analyzed the
distribution of passenger flow intuitively and scientifically, and predicted
the future trend of tourist flow in scenic spots, hoping to provide help for
the development of Shanghai tourism.
