USING ENN-1 TO INSPECT THE AIR POLLUTION OF AUTOMOBILE EXHAUST BY REMOTE SENSING DATA

摘要：

This research uses the extension neural network type-1 (ENN-1) method for air pollution inspected by remote sensing data of automobiles exhaust. The outdated automobiles emit exhaust as part of the moving air pollutants. To lessen the air pollution effectively and improve the efficiency of remote sensing tools, this paper develop a automatic inspected method based on the ENN-1 and using the data of automobile exhausted telemeter, the ENN-1 can embed the salient features of parallel computation and learning capability. The experimental results show that the proposed method has less learning time, high classificatory accuracy rate, and fault-tolerant than the other methods.

关键词： Extension Neural Network Air Pollution Classification Neural Network GA

作者: MENG-HUI WANG KUEI-HSIANG CHAO KENG-HSIEN LIN

作者单位: Institute of Information and Electrical Energy National Chin-Yi Institute of Technology, Taiwan

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3000-3005

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）