文献类型：会议论文

英文题名：Wireless Sensor Network for Community Intrusion Detection System Based on Improved Genetic Algorithm Neural Network

作者：Gao, Meijuan[1];Tian, Jingwen[1]

第一作者：高美娟

通讯作者：Gao, MJ[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：International Conference on Industrial and Information Systems

会议日期：APR 24-25, 2009

会议地点：Haikou, PEOPLES R CHINA

语种：英文

外文关键词：community; intrusion detection; wireless sensor network; genetic algorithm; neural network; face recognition

摘要：A community intrusion detection system based on improved genetic algorithm neural network (IGANN) is presented in this paper. This system is composed of ARM (Advanced RISC Machines) data acquisition nodes, wireless mesh network and control centre. The data acquisition node uses sensors to collect information and processes them by image detection algorithm, and then transmits information to control centre with wireless mesh network. When there is abnormal phenomenon, the system starts the camera and the IGANN is used to recognize the face image. The improved genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. With the ability of strong self-learning and pattern classification and fast convergence of IGANN, the recognition method can truly classify the face. This system resolves the defect and improves the intelligence and alleviates worker's working stress.