基于Python编程对我国生活垃圾热值的分析与预测

Analysis and Prediction of Calorific Value of MSW in China Based on Python Programme

生活垃圾设计热值是垃圾焚烧厂设计的重要依据。根据收集的我国已运行105座垃圾焚烧厂的年平均运营数据,对垃圾热值进行估算,基于Python编程对影响垃圾热值的16条因素进行了相关性分析。结果表明:我国垃圾热值南北(以33°N秦岭淮河为分界线)差异较大,且垃圾热值分布具有复杂性和非线性的特征。据此建立了我国垃圾热值非线性回归模型,该模型比线性回归模型预测精度提升了73%。

The design calorific value of MSW is an important basis for the design of waste incineration plants.According to annual average operation data of 105 waste incineration plants collected in China,calorific value of MSW was evaluated and correlational analyses of 16 impact factors on MSW calorific value were conducted based on python programme.The results revealed that the calorific value of MSW in China was of great difference between southern and northern(the boundary line is 33°N Qinling-Huaihe),and MSW calorific value distribution was complex and nonlinear.Based on this,the nonlinear regression model of China MSW calorific value were established,which improved the prediction accuracy by 73%compared with the linear regression model.