基于加权马尔可夫模型的径流预测研究.pdf

Journal of Water Resources Research 水资源研究, 2012, 1, 470-474 doi:10.4236/jwrr.2012.16075 Published Online December 2012 (/journal/jwrr.html) Application of Weighted Markov Chain Model to Predict * Runoff # Zhongling Hu, Bing Shen , Jiqiang Lv Key Lab of Northwest Water Resources and Environment Ecology, Xi’an University of Technology, Xi’an Email: lingzi902@126.com, #shenbing@ Received: Aug. 14th th th , 2012; revised: Aug. 29 , 2012; accepted: Sep. 7 , 2012 Abstract: This paper tries to take the Fuzzy C-Means method (FCM) to classify runoff state of Markov chain model. Then aiming at the runoff characteristics of dependent random variables and taking order of autocor- relation coefficients as the weights, Markov chain model is used to predict the following year runoff state. The runoff state from 2001-2004 are predict based on the 54 years annual runoff data from 1950-2004 at Ji- mai gauging station located in Dari country, Qinghai Province, the results are consistent with the actual situa- tion. That means the application of Markov chain model with FCM to determine runoff state of Jimai gauging station is feasible and effective. Keywords: FCM; Weighted Markov Chain; Autocorrelation Coefficient; Annual Runoff 基于加权马尔可夫模型的径流预测研究* # 胡忠玲，沈 冰 ，吕继强 西安理工大学西北水资源与环境生态教育部重点实验室，西安 Email: lingzi902@126.com, #shenbing@ 收稿日期：2012 年 8 月 14 日；修回日期：2012 年 8 月 29 日；录用日期：2012 年 9 月 7 日 摘 要：本文尝试应用模