Artificial neural network-based time series analysis forecasting for the amount of solid waste in Bangkok

Solid waste is a municipal environmental problem which difficult to manage. Thus, a solid waste forecasting model is essential for the effective management and planning. This paper aims to develop a time series forecasting model for the amount of solid waste generated in Bangkok using artificial neural networks, and offers a suitable model for solid waste forecasting. The time series data were collected as monthly accounts of solid waste generated between October 2002 and July 2013. Then, the data were cleaned and converted in order to accurately analyze. The forecast model was developed using predictive analytic tool Rapidminer. Artificial neural network model was trained with backpropagation algorithm. The results showed that the network structure of 3-35-1 performs the greatest performance with prediction accuracy at 0.870 and MSE equaling 0.2333.