南水北调与水利科技Issue(4)：618-621,4.DOI:10.13476/j.cnki.nsbdqk.2015.04.003
加权马尔可夫链模型在密云水库入库流量中的应用
Application of the weighted Markov chain model in the inflow prediction of the Miyun Reservoir
摘要
Abstract
According t o the act ual inflow data of the Miyun Reservoir from 1960 to 2011, river runoff was select ed as the random variable, and t he related concept of the w eighted Markov chain model and the st eps for the inflow prediction in the incoming one year w ere introduced. The classificat ion method of average-standard was used to divide the inflow sequence into four conditions, including drought, lean drought, lean wet, and w et. The autocorrelation w as regarded as weight coefficient to predict inflow be-tw een 2010 and 2011, which w ere compared w ith the measured data. T he results showed that the weighted Markov chain model can predict inflow of the Miyun Reservoir w it h high precision. Therefore, the model w as used to predict inf low betw een 2012 and 2013. Finally, the ergodicit y and stationary distribut ion of Markov chain were analyzed, and the return periods of observed sequence under the w et and dry condit ions w ere calculat ed, which suggested that the occurrence probability of lean drought is the largest. The inflow of the Miyun Reservoir was predicted to be lean drought in the future.关键词
加权马尔可夫链模型/密云水库/入库流量/转移概率矩阵/马氏性检验/自相关系数/偏枯Key words
w eighted Markov chain model/Miyun Reservoir/reservoir inflow/transit ion probabilit y matrix/Markov property tes-ting/autocorrelation coefficient/lean drought分类
建筑与水利引用本文复制引用
贺娟,王晓松,王彩云..加权马尔可夫链模型在密云水库入库流量中的应用[J].南水北调与水利科技,2015,(4):618-621,4.基金项目
北京市科技计划课题( Z141100006014049) （ Z141100006014049）
国家科技重大专项课题(2012ZX07205-005) （2012ZX07205-005）
