计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 391-393.
丁勇,朱辉生,曹红根
DING Yong,ZHU Hui-sheng and CAO Hong-gen
摘要： 首先提出一种改进的算法NONEPI++,用于挖掘事件序列上非重叠发生的频繁情节；然后将每个频繁情节表示为相应的情节隐马尔可夫模型EHMM,并通过最大期望算法计算模型的混合系数,从而生成一个基于历史数据流的混合模型；最后,基于该混合模型预测目标事件类型出现的概率。实验表明,混合EHMM模型能有效地预测数据流。
| [1] Manilla H,Toivonen H,Verkamo A．Discovering frequent episodes in sequences[C]∥Proceedings of the First International Conference on Knowledge Discovery and Data Mining．1995:210-215 [2] Mannila H,Toivonen H,Verkamo A I．Discovery of frequentepisodes in event sequences[J]．Data Mining and Knowledge Discovery,1997,1(3):259-289 [3] Mannila H,Toivonen H．Discovering Generalized Episodes U-sing Minimal Occurrences[C]∥KDD．1996:146-151 [4] Laxman S,Sastry P S,Unnikrishnan K P．Discovering frequent episodes and learning hidden markov models:A formal connection[J]．IEEE Transactions on Knowledge and Data Engineering,2005,17(11):1505-1517 [5] Fletcher A K,Rangan S,Goyal V K．Estimation from lossy sensor data:Jump linear modeling and Kalman filtering[C]∥Proceedings of the 3rd international symposium on Information processing in sensor networks．ACM,2004:251-258 [6] Cho C W,Zheng Y,Wu Y H,et al．A tree-based approach for event prediction using episode rules over event streams[C]∥Database and Expert Systems Applications．Berlin Heidelberg:Springer,2008:225-240 [7] 朱辉生,汪卫,施伯乐．基于情节规则匹配的数据流预测[J]．软件学报,2012,23(5):151-162 [8] 王志超,刘惠义．一种基于隐马尔可夫模型的人脸识别方法[J]．计算机应用与软件,2013,30(2):304-307 [9] 肖献强,任春燕,王其东．基于隐马尔可夫模型的驾驶行为预测方法研究[J]．中国机械工程,2013,24(21):2972-2976 [10] 闫新娟,谭敏生,严亚周,等．基于隐马尔科夫模型和神经网络的入侵检测研究[J]．计算机应用与软件,2012,29(2):294-297 [11] 吕岸,胡振程,陈慧．基于高斯混合隐马尔科夫模型的高速公路超车行为辨识与分析[J]．汽车工程,2010(7):630-634 |
| No related articles found! |
|
||
首页