Marine traffic accident prediction based on particle swarm optimization-based RBF neural network

摘要：

The future marine traffic accident situation is shown by using the marine traffic accident prediction method. Thus, marine traffic accident prediction method based on particle swarm optimization-based RBF neural network is presented in the paper. Particle swarm optimization algorithm, a kind of populationbased optimization algorithm, is used to adjust the connection weights and the center and width of radial basis function.The marine traffic accidents of a certain terminal from 1996 to 2007 are applied to study the feasiblity of the proposed PSO-RBF neural network.The comparison reuslts between the proposed PSO-RBF neural network and normal RBF neural network can indicate that the prediction results of marine traffic accidents of the proposed PSO-RBF neural network are better than those of RBF neural network.

关键词： marine traffic accident particle swarm optimization prediction model neural network

作者: YANG Zhen-Qi

作者单位: Shandong Jiaotong University Jinan 250023, China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 435-438

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）