Forecasting the electronic waste quantity with a decomposition-ensemble approach

Abstract

Waste electrical and electronic equipment (viz., WEEE or e-waste) is the fastest-growing type of hazardous solid waste in the worldwide. The accurate prediction of the amount of e-waste might help improve the efficiency of e-waste disposal. In this study, a novel decomposition-ensemble-based hybrid forecasting methodology that integrates variational mode decomposition (VMD), exponential smoothing model (ESM), and grey modeling (GM) methods (named VMD-ESM-GM) is proposed for e-waste quantity prediction. For verification purposes, sample data from Washington State, US, and UK Environment Agency are analyzed. Compared to benchmark models, the proposed VMD-ESM-GM methodology not only obtains a satisfactory prediction result for e-waste data but also predicts the future fluctuation trend of e-waste. These results indicate that the proposed VMD-ESM-GM methodology based on the decomposition-ensemble principle is a suitable model for the prediction of the e-waste quantity and could help decision-makers develop both e-waste recycling plans and circular economy plans.

Keywords: Decomposition-ensemble Approach; E-waste Forecasting; Grey Modeling.