西安市城市生活垃圾产生量的多元回归及ARIMA模型预测  

Multiple Regression and ARIMA Model Prediction on the Yield of MSW in Xi’an

作　　者：杨小妮[1,2] 张凯轩[1] 杨宏刚 于媛[1] Yang Xiaoni;Zhang Kaixuan;Yang Honggang;Yu Yuan(Huaqing College,Xi’an University of Architecture and Technology,Xi’an Shaanxi 710043;College of Environment and Municipal Engineering,Xi’an University of Architecture&Technology,Xi’an Shaanxi 710055;College of Resource Engineering,Xi’an University of Architecture and Technology,Xi’an Shaanxi 710055)

机构地区：[1]西安建筑科技大学华清学院,陕西西安710043 [2]西安建筑科技大学环境与市政工程学院,陕西西安710055 [3]西安建筑科技大学资源工程学院,陕西西安710055

出　　处：《环境卫生工程》2020年第2期37-41,共5页Environmental Sanitation Engineering

基　　金：西安建筑科技大学人才科技基金项目(RC1831);陕西省高等教育学会2019年度高等教育科学研究项目(XGH19253)。

摘　　要：基于西安市历年来城市生活垃圾产生量及其影响因素的基础数据,通过对其相关系数的计算,确定西安市城市生活垃圾产生量的主要影响因素为人口数量、地区生产总值、城镇居民可支配收入及建成区面积。建立生活垃圾产生量的多元回归预测模型,对模型的合理性和精度进行分析,预测精度可接受,证明多元回归模型可用于城市生活垃圾产生量的预测。引入ARIMA模型,对所需因子进行预测,应用多元回归模型,对西安市2019—2020年的生活垃圾产生量进行了预测,结果表明,2019—2020年西安市城市生活垃圾产生量将分别达到4.922×106 t、5.219×106 t,且这2 a的垃圾产生量增长率将达到6.0%。Based on the basic data of the yield of municipal solid waste(MSW)and its influencing factors in Xi'an over the years,through the calculation of its correlation coefficient,the main influencing factors of the yield of MSW in Xi'an were confirmed,including population,gross regional production,disposable income of urban residents and area of urban construction.The multiple regression prediction model of the yield of MSW was established,and its rationality and precision were analyzed.The prediction accuracy was accepted,which proved that the multiple regression model could be used to predict the yield of MSW.The ARIMA model was introduced to predict the required factors,and the multiple regression model was applied to predicted the yield of MSW in Xi'an from 2019 to 2020.The results showed that the yield of MSW in Xi'an would reach 4.922×106,5.219×106 t respectively from 2019 to 2020.Moreover,the growth rate of the yield of MSW in these two years would reach to 6.0%.

关 键 词：城市生活垃圾 多元线性回归模型 ARIMA模型 产生量 

分 类 号：X799.3[环境科学与工程—环境工程]