【作者】 刘保政； 汪定伟；

【Author】 LIU Bao-zheng;WANG Ding-wei;College of Mathematics Science, Liaocheng University;College of Information Science & Engineering, Northeastern University;

【机构】 聊城大学数学科学学院； 东北大学信息科学与工程学院系统工程研究所；

【摘要】 基于数据挖掘对城市生活用水量的主要影响因子进行了灰色关联分析比较,探讨城市生活用水量的主要驱动因子;通过对主要影响因子发展趋势的灰色预测,建立了关于城市生活年度用水量的驱动因子灰预测GM(0,N)模型.实例证明拟合数据效果良好.该模型以城市人口和城市居民人均可支配收入为自变量,作为主要影响因子对城市生活用水量进行近期和中期预测.最后提出了减缓城市水危机的建议和有效措施.更多还原

【Abstract】 Based on data mining, the main impact factors of urban life water consumption are made gray relational analysis with the water consumption. The main driving factors of urban life water consumption are discussed. By the gray forecasting of the development trends of the main impact factors, a grey prediction of GM(0, N) model on urban life water is established. An instance proves to fit the data better. The model is based on the short and medium term forecasts of urban population and per capita disposable income to predict the urban life water annual consumption. Finally, the recommendations and effective measures to mitigate the urban water crisis are proposed.更多还原