Study On Prediction Model Of Municipal Solid Waste Transportation Amount And Composition

With the development of social economy and the improvement of living standards, especially the development of urbanization process, the generation of municipal solid waste (MSW) in China is rapidly increasing, and the composition of MSW has changed. Municipal solid waste gradually become an very important threat of urban environmental sanitation and resident health, and restrict the sustainable development of the society, economy and environment. Successful planning and operation of a municipal solid waste management system depends on accurate predictions of MSW transportation amount and composition.The influence factors of MSW transportation amount and composition were analyzed. The grey correlation analysis method was applied to analyze contribution level of the influence factors on MSW transportation amount and composition to determine the main influence factors of MSW.A BP neural network prediction model of MSW transportation amount and composition was set up, and the main influence factors of MSW determined by grey correlation analysis were chosen as the input vectors of BP neural network.The case study on Shanghai showed a high accuracy between the predicted and measured values by calculated MAPE and EC of the prediction model. MSW transportation amount and composition in Shanghai from 2007 to 2010 were predicted.The result indicated that prediction model based on grey relational degree and BP Neutral Network can predict MSW delivering quantity and composition, and was proved to be feasible and suitable.