Marine traffic accident prediction based on particle swarm optimization-based RBF neural network
作者
Yang Zhen-qi
标识
DOI:10.1109/iccrd.2011.5764052
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 population-based 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 feasibility of the proposed PSO-RBF neural network. The comparison results 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.