复权马尔可夫链及其在怒江水沙预测中的应用

发布时间：2018-06-24 01:57

  本文选题：复权马尔可夫链 + 数值预测　； 参考：《南水北调与水利科技》2017年06期

【摘要】：针对传统马尔可夫链及其改进的预测方法只能进行状态预测的局限,根据相依随机变量的特点,在以传统马尔可夫链预测方法求得各状态预测概率的基础上,进一步以状态预测概率为权重与状态平均值加权求和,实现了马尔可夫链预测方法从状态预测到数值预测的关键性改进。利用我国西南国际大河怒江干流道街坝水文站1957-2010年径流和1964-2010年悬移质输沙序列为分析期,2011-2015年径流和悬移质输沙为验证期,对所建立的复权马尔可夫链预测方法步骤进行验证表明,复权马尔可夫链预测方法具有较高的数值预测精度,能够满足随机时间序列短期数值预测的需要。
[Abstract]:According to the characteristics of the traditional Markov chain and its improved prediction method, according to the characteristics of the dependent random variables, the Markov chain preview is realized on the basis of the traditional Markov chain prediction method, and the state prediction probability is weighted and the state mean value is weighted. The method from state prediction to numerical prediction is a key improvement. The 1957-2010 year runoff and 1964-2010 year suspended sediment transport sequence in the main stream Road dam of Nu River in the southwest of our country are used as the analysis period, and the 2011-2015 year runoff and suspended sediment transport is the verification period. The results show that the prediction method of complex Markov chain has higher numerical prediction accuracy and can meet the needs of short-term numerical prediction of random time series.
【作者单位】： 河海大学水文水资源与水利工程科学国家重点实验室;云南省滇中引水工程建设管理局昆明分局;云南财经大学国土资源与持续发展研究所;云南省水文水资源局;
【基金】：江苏省博士后科研资助计划(1501060B) 云南省水利科技项目(2014003)~~
【分类号】：P333
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本文编号：2059465