Forecasting municipal solid waste generation based on grey fuzzy dynamic modeling

There has been a significant increase in municipal solid waste generation in China during the last few decades. Both planning and design of municipal solid waste management systems require accurate prediction of solid waste generation. The lack of complete historical records of solid waste quantity and quality due to insufficient budget and unavailable management capacity has resulted in a situation that makes the long-term system planning and/or short-term expansion programs intangible. To effectively handle these problems based on limited data samples, a new analytical approach capable of addressing socioeconomic and environmental situations must be developed and applied for fulfilling the prediction analysis of solid waste generation with reasonable accuracy. This study presents a new approach -grey fuzzy dynamic modeling- for the prediction of solid waste generation in a fast-growing urban area based on a set of limited samples. The practical implementation has been accessed by a case study in the city of Beijing in China. It shows that such a new forecasting technique may achieve better prediction accuracy than those of the conventional grey dynamic model, least-squares regression method, and the fuzzy goal regression technique.