期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：42
期号：1
页码：132-136
出版社：Journal of Theoretical and Applied
摘要：The data mining is carried out for the historical data to investigate and analyze crucial factors related to the causes of accidents of fishing boats. The vital factors, especially shipping time, weather and manipulation, etc. are extracted as the input variables of a BP neural network to establish a safety warning model for fishing boats. In addition, the Particle Swarm Optimization (PSO) is employed to develop the generalization ability of neural network and optimize the parameters of safety warning model. Experiments using the historical data have showed high efficiency of the proposed intelligent safety warning model. Hence, it is feasible for the design of waterborne traffic safety and warning system.
关键词：Fishing Boats; Safety Regulation and Warning; Neural Network
