基于随机森林回归算法的用水总量影响因素解析——以广东省为例

通过构建包含人口、水资源、技术和经济4项因素和常住总人口、人口密度、水资源总量、降雨量、万元GDP用水量、万元工业增加值用水量、第一产业生产总值、第二产业生产总值和第三产业生产总值9个元素的层次评价体系,采用熵值法和随机森林回归算法,以广东省21个地级市为例,分析广东省用水总量的影响因素.研究结果表明:(1)从元素层角...

An Analysis of the Factors in Total Water Consumption Based on Random Forest Regression Algorithm: A Case Study of Guangdong Province

A hierarchical evaluation system is constructed, including four factors (i.e., population, water resources, technology and economy) and nine elements (i.e., total resident population, population density, total water resources, rainfall, water consumption per 10 000 yuan of GDP, water consumption per 10 000 yuan of industrial added value, gross product of the primary industry, gross product of the secondary industry and gross product of the tertiary industry). The entropy method and the random forest regression algorithm are adopted to analyze the factors in the total water consumption in 21 prefecture-level cities in Guangdong Province. Three major results are obtained. First, in the element perspective, the total resident population, the gross product of the tertiary industry and the gross product of the primary industry are the main elements in the total water consumption in Guangdong Pro-vince, while rainfall has the least influence on the total water consumption of the prefecture-level cities in Guangdong Province. Second, in the factor perspective, the influence of the four factors on the total water consumption in Guangdong Province is in descending order: economic factors, population factors, water resources factors and technical factors. Third, based on the element and factor analysis, it can be seen that among the factors of population, water resources, technology and economic, the biggest elements that affect the total water consumption of Guangdong Province are the total resident population, total water resources, water consumption of 10 000 yuan per industrial added value and the gross product of the tertiary industry.