| Title |
Forecasting the electronic waste quantity with a decomposition-ensemble approach |
| ID_Doc |
29484 |
| Authors |
Wang, F; Yu, L; Wu, AP |
| Title |
Forecasting the electronic waste quantity with a decomposition-ensemble approach |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.wasman.2020.11.006 |
| 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. (C) 2020 Elsevier Ltd. All rights reserved. |
| Author Keywords |
E-waste Forecasting; Grey Modeling; Decomposition-ensemble Approach |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000604340900022 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
|