Development of a hybrid model to predict construction and demolition waste: China as a case study

被引:47
|
作者
Song, Yiliao [1 ]
Wang, Yong [1 ,2 ]
Liu, Feng [1 ]
Zhang, Yixin [3 ]
机构
[1] Dongbei Univ Finance & Econ, Sch Stat, Dalian 116025, Peoples R China
[2] Dongbei Univ Finance & Econ, Postdoctoral Res Stn, Dalian, Peoples R China
[3] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China
基金
中国国家自然科学基金;
关键词
Construction and demolition waste; Forecasts; GM-SVR; MANAGEMENT; REDUCTION;
D O I
10.1016/j.wasman.2016.10.009
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Construction and demolition waste (C&DW) is currently a worldwide issue, and the situation is the worst in China due to a rapid increase in the construction industry and the short life span of China's buildings. To create an opportunity out of this problem, comprehensive prevention measures and effective management strategies are urgently needed. One major gap in the literature of waste management is a lack of estimations on future C&DW generation. Therefore, this paper presents a forecasting procedure for C&DW in China that can forecast the quantity of each component in such waste. The proposed approach is based on a GM-SVR model that improves the forecasting effectiveness of the gray model (GM), which is achieved by adjusting the residual series by a support vector regression (SVR) method and a transition matrix that aims to estimate the discharge of each component in the C&DW. Through the proposed method, future C&DW volume are listed and analyzed containing their potential components and distribution in different provinces in China. Besides, model testing process provides mathematical evidence to validate the proposed model is an effective way to give future information of C&DW for policy makers. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:350 / 361
页数:12
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