ANN-based Multi Classifier for Identification of Perimeter Events

摘要：

Identification of perimeter events enables smarter perimeter security systems. This paper presents a multi classifier. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the bottom to build the classifier. The top level employs voting mechanism to identify intrusions, taking time evolution characters into account. In addition, to make the classifier be more self-adaptive, an incremental learning module is introduced. The proposed classifier has been successfully applied to oil and gas pipeline intrusion detection systems. Practical results show that it can distinguish nuisance events from intrusion events at a high rate of 94.86％ and for seven kinds of intrusions, the recognition rate is 95.29％, fully satisfies the real application requirement.

关键词： Perimeter Intrusion detection Artificial neural network Support vector machine Vibration signal Smart

作者: Hu Yan Lixin Li Fangchun Di Jin Hua Qiqiang Sun

作者单位: China Electric Power Research Institute Beijin, China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 538-541

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）