加权马尔可夫链在新疆阿克苏河年径流量预测中的应用

径流预测在水资源规划中发挥着重要作用.基于径流过程不确定性、不精确性的特点,利用资料系列的均方差方法把径流序列分为不同的状态.在此基础上,采用统计方法,建立转移概率矩阵,以规范化的各阶自相关系数为权重.用加权马尔可夫模型预测径流状态,并根据模糊集理论中的级别特征值预测径流量,最后把加权马尔可夫预测模型应用于新疆阿克苏河径流丰枯状态及年径流量的预测中,结果令人满意.

Application of Weighted Markov Chain Method in Annual Runoff Prediction of Akesu River of Xinjiang

Runoff prediction plays an important role in water resources planning.According to the uncertainty and inaccuracy characteristics of runoff process,the runoff series could be divided into different states through mean square deviation method of data series.Based on it,transition probability matrix is obtained by using statistical method.Standardized sell-correlative coefficients,which are based on the special characteristics of correlation among the historical stochastic variables,are regarded as weight values.The method of weighted Markov chain is used to predict the future runoff state,and the level characteristic value of fuzzy sets is used to predict the concrete value of runoff.In the end,as an example,the improved model is applied to predict annual runoff of Akesu River,and the results are satisfactory.