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借助于MATLAB软件,对中国31个地区旅游业发展规律进行动态聚类分析及综合评价。根据中国2000-2009年31个地区旅游总收入的5个影响因素(旅客周转量、旅行社单位数、城镇居民人均收入、各地区国内生产总值、城区面积)数据,进行欧氏距离聚类分析,把31个地区分为3类,即总收入较高区、总收入中等区和总收入较低区,所得结果与客观实际符合。利用聚类的结果,运用马氏链模型预测未来两年31个地区旅游业总收入的发展趋势。
With the help of MATLAB software, the dynamic cluster analysis and comprehensive evaluation of tourism development in 31 regions in China are carried out. According to the five influencing factors (passenger turnover, number of travel agencies, per capita income of urban residents, GDP of each region, urban area) of 31 regions in China from 2000 to 2009, the Euclidean distance cluster analysis 31 regions were classified into 3 categories, namely, the areas with higher total income, medium income area and lower total income area. The results obtained are in line with the objective reality. Using the result of clustering, the paper uses Markov chain model to predict the development trend of total tourism revenue in 31 regions in the next two years.