基于Lasso回归和ARIMA模型的城市生活垃圾产生量预测——以宝鸡市为例  

Prediction of Municipal Solid Waste Production Based on Lasso Regression and ARIMA Model:Taking Baoji as an Example

作　　者：房妮[1] 俱国鹏[1] 惠姣姣 雷霁 FANG Ni;JU Guopeng;HUI Jiaojiao;LEI Ji(Shaanxi Key Laboratory of Disaster Monitoring&Mechanism Simulation,Baoji University of Arts and Sciences,Baoji 721016,Shannxi China;School of Mathematics and Information Science,Baoji University of Arts and Sciences,Baoji 721016,Shannxi China)

机构地区：[1]宝鸡文理学院陕西省灾害监测与机理模拟重点实验室,陕西宝鸡721016 [2]宝鸡文理学院数学与信息科学学院,陕西宝鸡721016

出　　处：《河南科学》2022年第1期98-103,共6页Henan Science

基　　金：陕西省教育厅专项科学研究计划(17JK0046);宝鸡文理学院博士启动经费校级科研项目(ZK2018048)。

摘　　要：基于宝鸡市2009—2019年城市生活垃圾产生量及其影响因素的基础数据,首先通过Lasso回归建立了生活垃圾产生量预测模型,其次通过ARIMA模型对模型中主要影响因子进行了预测,最后通过Lasso模型对2020—2025年宝鸡市城市生活垃圾产生量进行了预测.结果表明,Lasso回归模型预测精度高,可用于城市生活垃圾产生量的精准预测.未来几年宝鸡市生活垃圾产生量将会快速增长,2025年将达到的52.71×10^(4)t.Based on the basic data of municipal solid waste(MSW)production and its influencing factors in Baoji from 2009 to 2019,the prediction model of the yield of MSW was established by Lasso regression,and the main influencing factors in the model were predicted by ARIMA model. Finally,the Lasso model was used to forecast MSW production in Baoji from 2020 to 2025. The results show that the Lasso regression model has high prediction accuracy,which can be used to accurately predict the yield of MSW. In the next few years,the MSW output of Baoji will increase rapidly,and it will reach 52.71×10^(4) t in 2025.

关 键 词：生活垃圾产生量 Lasso回归 ARIMA模型 预测 

分 类 号：X799.3[环境科学与工程—环境工程]