Utility water supply forecast via a GM (1,1) weighted Markov chain
Utility water supply forecast via a GM (1,1) weighted Markov chain
复制标题
通过 GM (1,1) 加权马尔可夫链预测公用事业供水
DOI：
10.1631/jzus.a0900754
复制
发表时间：
2010-09
影响因子：
3.2
通讯作者：
Shen, Hai-liang
中科院分区：
文献类型：
--
作者：
Tian, Yi-mei;Zhang, Li;Lv, Xiang-rui;Shen, Hai-liang
This paper describes the procedure of using the GM (1,1) weighted Markov chain (GMWMC) to forecast the utility water supply, a quantity that usually has significant temporal variability. The GMWMC is formulated into five steps: (1) use GM (1,1) to fit the trend of the data, and obtain the relative error of the fitted values; (2) divide the relative error into ‘state’ data based on pre-set intervals; (3) calibrate the weighted Markov chain model: herein the parameters are the pre-set interval and the step of transition matrix (TM); (4) by using auto-correlation coefficient as the weight, the Markov chain provides the prediction interval. Then the mid-value of the interval is selected as the relative error for the data. Upon combining the data and its relative error, the predicted magnitude in a specific time period is obtained; and, (5) validate the model. Commonly, static intervals are used in both model calibration and validation stages, usually causing large errors. Thus, a dynamic adjustment interval (DAI) is proposed for a better performance. The proposed procedure is described and demonstrated through a case study, which shows that the DAI can usually achieve a better performance than the static interval, and the best TM may exist for certain data.
登录
查看更多内容
影响因子：
1
作者：
L. Pau
通讯作者：
L. Pau
影响因子：
3.9
作者：
Gwo-Ching Liao;T. Tsao
通讯作者：
Gwo-Ching Liao;T. Tsao
DOI：
--
发表时间：
2007
期刊：
--
影响因子：
--
作者：
Zhang Sen
通讯作者：
Zhang Sen
DOI：
10.1016/j.techfore.2020.120166
发表时间：
2020-09-01
影响因子：
12
作者：
Chang, Victor;Baudier, Patricia;Arami, Mitra
通讯作者：
Arami, Mitra
DOI：
--
发表时间：
2006
期刊：
Ground Water
影响因子：
--
作者：
Gong Lin-lin
通讯作者：
Gong Lin-lin