Water Demand Prediction of Grey Markov Model Based on GM(1, 1)

摘要

When the raw data has greater volatility, alone using GM (1, 1) model can lead to big error of water demand prediction results. For this problem, based on the grey GM (1, 1) model and Markov model theory and combine the two algorithm to constitute a grey Markov model which is reasonable and applied to the domestic water demand forecasting project of water supply area in the JV Company of Tianjin. Results show that in the case of original data volatile grey Markov model overcomes the disadvantages of grey GM (1, 1) model and the insufficiency, improves the prediction precision, and enhances the scientific nature and reliability of results.