Prediction analysis of solid waste generation based on grey fuzzy dynamic modeling

Successful planning of a solid waste management system depends critically on the prediction accuracy of solid waste generation. But the prediction condition of generation trend in many developing countries is quite different from those in developed countries. The lack of sampling and analysis in many developing countries due to insufficient budget and unavailable management task force has resulted in a situation where the historical record of solid waste generation and composition can never be completed in the long term. To effectively handle these problems with only limited samples and fulfil the prediction analysis of solid waste generation with reasonable accuracy, a special analytical technique must be developed and applied before the subsequent system planning for urban solid waste management is carried out. This study presents a new theory — grey fuzzy dynamic modeling — for the prediction of solid waste generation in the urban area based on a set of limited samples. The practical implementation has been accessed by a case study in the city of Tainan in Taiwan. 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. © 2000 Elsevier Science B.V. All rights reserved.