Combined weight-varying model for production prediction of residential solid waste: a case study of Xiamen

DOI

10.2991/icemet-16.2016.417How to use a DOI?

Keywords

combined weight-varying model; residential solid waste; linear fit; exponential smoothing.

Abstract

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..

Copyright

© 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/).

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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  - 10.2991/icemet-16.2016.417
ID  - Liu2016/05
ER  -