摘要
从目标的活动过程中提取目标活动特征,是分析目标活动的基础。为了降低目标活动特征的复杂性,分析了一种活动特征提取方法。该方法以目标活动的状态参数序列为基础,先将目标的活动状态参数划分为短序列集后,对其进行数据清洗,再从中计算得到目标活动的分类规则,最后从规则匹配结果中提取目标的活动特征序列。通过仿真实验,验证了该算法的可行性和有效性。
Extracting the activity characteristic from the target＇s activity process is fundamental to analyze the target activity. In order to minimize the complexity of analysis, the paper introduces an algorithm of activity characteristic extracted. In this method, target activities state parameter is divided into short sequences episodes, the data clean is performed for them, then the classification rules of target activities are obtained by calculating, finally the activity characteristic sequence of target is extracted from rule matching result. Simulation experiments show that this algorithm has feasibility and efficiency.
出处
《计算机与网络》
2011年第9期54-56,共3页
Computer & Network
关键词
活动特征
数据清洗
规则匹配
活动特征序列
activity characteristic, data cleaning, rules matching, activity characteristic sequence
