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加权马尔可夫模型在降水丰枯状况预测中的应用
引用本文:孙才志,张戈,林学钰. 加权马尔可夫模型在降水丰枯状况预测中的应用[J]. 系统工程理论与实践, 2003, 23(4): 100-105. DOI: 10.12011/1000-6788(2003)4-100
作者姓名:孙才志  张戈  林学钰
作者单位:(1)辽宁师范大学城市与环境学院; (2) 吉林大学资源与环境学院
基金项目:国家重点基础研究项目— 973项目(G19990 43 60 6),辽宁省自然科学基金 (0 0 10 63)
摘    要:首先基于降水过程存在大量不确定性、不精确性的特点 ,应用有序聚类的方法建立降水丰枯状况的分级标准 ;然后针对降水量为相依随机变量的特点 ,采取以规范化的各阶自相关系数为权重 ,用加权的马尔可夫链模型来预测未来降水的丰枯变化状况 ;最后以山西省某水文站近 5 0年的降水资料为实例对该方法进行了具体的应用 ,获得了较为满意的结果.

关 键 词:降水  有序聚类    马尔可夫链  预测   
文章编号:1000-6788(2003)04-0100-06
修稿时间:2001-12-06

Model of Markov Chain with Weights and Its Application in Predicting the Precipitation State
SUN Cai-zhi ,ZHANG Ge ,LIN Xue-yu. Model of Markov Chain with Weights and Its Application in Predicting the Precipitation State[J]. Systems Engineering —Theory & Practice, 2003, 23(4): 100-105. DOI: 10.12011/1000-6788(2003)4-100
Authors:SUN Cai-zhi   ZHANG Ge   LIN Xue-yu
Affiliation:(1) Urban and Environment Institute,Liaoning Normal University;(2)Resources and Environment Institute,Jilin University
Abstract:This paper firstly applied sequential cluster method to set up the classification standard of precipitation state based on the fact that there are much uncertainty and imprecise characteristics in the precipitation course; then this paper presented a method which is called Markov chain with weights to predicted the future precipitation state by regarding the standardized self-coefficients as weights based on the special characteristics of precipitation being a dependent stochastic variable; and applied this method to a real hydrological observation station with nearly 50 years precipitation information in Shanxi Province at last, an ideal result was obtained.
Keywords:precipitation  sequential cluster  weight  Markov chain  prediction
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