Evaluation of different curve fitting models for prediction of municipal solid waste composition

In this study, the methodology was applied for the prediction of municipal solid waste (MSW) composition in the Eskişehir/Turkey. For this purpose, MSW samples were collected, and the samples were separated by food wastes, paper-cardboard, plastics, glass, metals as manually. In the present study, the concept of 2D curve fitting functions was adopted for the forecasting of MSW composition. To comment on the performance of proposed system, the Root Mean Square Error (RMSE) and Sum of Squared Error (SSE) metrics were chosen as statistical residual evaluation metrics. According to results, it is seen that the polynomial curve fitting model is most suitable. Also, the effect of socio-economic structure on the waste composition by different nonlinear models was observed. With contribution of study, it would be possible to forecast the MSW composition of other cities which have similar factors.