Study On Optimization Of Municipal Solid Waste Grey Forecasting Model

The development of urbanization and industrialization promotes economic growth and social advancement in China. Meanwhile, it also leads to urban population explosion as well as significant increase of municipal solid waste(MSW). In result, it is even more difficult for the existing MSW treatment infrastructure to deal with the MSW collected. Thus, MSW treatment infrastructure should be redesigned, accurate forecasting of MSW generation plays a key role. MSW forecasting is an important process in MSW management. Reliable prediction of future MSW quantities raises the effectiveness of continuous management planning and makes for MSW management. MSW projection results are often used to provide justi?cation for speci?c MSW policy measure formulation and in the planning of MSW treatment and recycling facilities and collection service. Equipped with an accurate projection of the waste type and their quantities, policy makers are then able to understand the dimension and scale of the problem and make informed decisions.This study aims to forecast MSW by using optimized grey model. The representative factors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory, then nonlinear optimized GM(1,N) model is built on basis of this and is used to forecast MSW collected in Kunming in short time period. Results are compared with that of traditional grey models, such as GM(1,1) and GM(1,N). Results show that the optimized GM(1,N) model is the most accurate both in fitting and forecasting. It shows the feasibility and optimization of this model.