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近年来,基于绝对分布的马尔可夫链预测(ADMCP)方法、叠加马尔可夫链预测(SPMCP)方法和加权马尔可夫链预测(WMCP)方法在各种水文序列预测理论中得到了广泛的应用。然而,实际生活中仅仅预测出状态区间是不够的,文章给出一种基于马氏链状态预测方法的点值预测方法,并将其与普遍接受的时间序列分析预测方法进行了基于统计试验的比较分析,得出了该方法在水文序列预测中较优的结论。
In recent years, the Markov chain prediction based on absolute distribution (ADMCP) method, the superposition Markov chain prediction (SPMCP) method and the weighted Markov chain prediction (WMCP) method have been widely used in various hydrological sequence prediction theories application. However, it is not enough to predict the state interval only in real life. In this paper, a method of point value prediction based on Markov chain state prediction is presented and compared with the commonly accepted method of time series analysis and prediction based on statistical tests Through comparative analysis, we conclude that this method is superior to hydrological sequence prediction.