elsevier期刊论文格式

Mining regular behaviors based on multidimensional trajectoriesXinlong Pan; You He; Haipeng Wang; Wei Xiong; Xuan Peng;Institute of Information FusionNaval Aeronautical and Astronautical UniversityYantai 264001ChinaABSTRACT:Abstract(#br)In the information fusion domain, mining regular behaviors is very important to task classification, anomaly behavior detection, situation assessment and threat estimation. Through clustering multidimensional trajectories which are accumulated in all kinds of electronic information systems, regular behaviors could be mined. Most of the trajectories clustering methods are clustering spatial position closed trajectories to a cluster. They cannot distinguish behaviors whose space posit... KEYWORDS:Regular behavior; Clustering; Multidimensional trajectory; Hausdorff distance;JOURNAL:Expert Systems With ApplicationsSOURCE:ElsevierjournalDOI:10.1016/j.eswa.2016.09.015YEAR:2016PAGES:106-113PUBLISHER:Elsevier Ltd基于多维轨迹的规则行为挖掘新龙盘; 你他; 王海鹏; 魏雄; 玄鹏;信息融合研究所海军航空航天大学烟台264001中国摘要：摘要在信息融合领域，挖掘规则行为对于任务分类、异常行为检测、态势评估和威胁估计具有重要意义。通过对各种电子信息系统中积累的多维轨迹进行聚类，挖掘出有规律的行为。大多数轨迹聚类方法是对聚类空间位置封闭轨迹进行聚类。他们分辨不出太空存在的行为.。更多关键词：有规律的行为；聚类；多维轨迹；Hausdorff距离；日刊：专家系统及其应用资料来源：ElsevierJournalDOI：10.1016/j.eswa.2016.09.015年份：2016页：106-113出版商：埃尔塞维尔有限公司