Combined weight-varying model for production prediction of residential solid waste: a case study of Xiamen
- https://doi.org/10.2991/icemet-16.2016.417How to use a DOI?
- combined weight-varying model; residential solid waste; linear fit; exponential smoothing.
The problem of residential solid waste (RSW) has drawn increasing attention. It is important to accurately predict the amount of RSW for planning solid waste management. In this research, a combined weight-varying model was presented based on logarithm fit, linear fit, exponential smoothing, and grey prediction GM(1, 1). The optimal weights in combined weight-varying model were determined in accordance with the amount of RSW in Xiamen City from 2009 to 2014 and the production from 2015 to 2024 had been predicted. The results showed that combined weight-varying model performed very well at prediction precision and the amount of RSW in Xiamen City would likely be 2.40 to 2.90 million tons..
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zheng Liu AU - Haiyan Fu AU - Aili Yang AU - Huiyan Cheng PY - 2016/05 DA - 2016/05 TI - Combined weight-varying model for production prediction of residential solid waste: a case study of Xiamen BT - Proceedings of the 2016 International Conference on Economy, Management and Education Technology PB - Atlantis Press SP - 1817 EP - 1820 SN - 2352-5398 UR - https://doi.org/10.2991/icemet-16.2016.417 DO - https://doi.org/10.2991/icemet-16.2016.417 ID - Liu2016/05 ER -