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贝叶斯网络参数的在线学习算法及应用
Application of Online Learning Algorithm for Bayesian Network Paramter
【摘要】 以 EM算法为基础 ,在给定贝叶斯网络结构情况下 ,研究分析了 Voting EM算法并利用该算法对防洪决策贝叶斯网络进行在线参数学习 ,将该算法与 EM算法的学习结果进行了比较分析 ,结果表明 Voting EM算法不但能够进行在线参数学习 ,而且也具有较高的学习精度
【Abstract】 A Voting EM algorithm which is based EM is discussed and applied in the parameter online learning in flood decision supporting Bayesian networks in this paper. Both EM algorithm and Voting EM are applied in flood decision Bayesian networks to compare their performance. The result indicates that the Voting EM can be used in online learning for Bayesian network parameter and it also has more precisely than traditional EM algorithm.
【关键词】 贝叶斯网络;
参数学习;
EM算法;
VotingEM算法;
【Key words】 bayesian networks; parameter learning; EM algorithm; Voting EM algorithm;
【Key words】 bayesian networks; parameter learning; EM algorithm; Voting EM algorithm;
- 【文献出处】 小型微型计算机系统 ,Mini-micro Systems , 编辑部邮箱 ,2004年10期
- 【分类号】TP18
- 【被引频次】21
- 【下载频次】540