Study on Prediction of Domestic Water Consumption Based on Residual Grey Markov Chain Model
Aiming at the problems of traditional GM (1,1) model in forecasting non-growth sequences in terms of water consumption,such as poor precision and over-fitting,a residual grey prediction model corrected with Markov chains is used to predict domestic water consumption.Based on the traditional grey pre...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Pearl River
2020-01-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2020.08.001 |
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| Summary: | Aiming at the problems of traditional GM (1,1) model in forecasting non-growth sequences in terms of water consumption,such as poor precision and over-fitting,a residual grey prediction model corrected with Markov chains is used to predict domestic water consumption.Based on the traditional grey prediction model,this paper firstly establishes an improved residual grey prediction model as follows:establish grey model on the absolute residual,and judge the sign of the predictive residual when t＞n based on Markov state transition matrix to correct the predictive value from grey model,and then apply the model to the prediction of domestic water consumption in Henan Province from 2007 to 2018.The results show that the average relative error of the traditional grey prediction model is 4.14%,while that of the improved residual grey prediction model is only 2.04%.The precision class of improved residual grey prediction model is “good”,meanwhile,the posterior variance of improved model is also smaller than that of the traditional model,which indicating that the improved model has higher precision and better reliability than the traditional grey prediction model,therefore,it is a new method for water consumption prediction. |
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| ISSN: | 1001-9235 |