Research on Risk Assessment of Waterway Dangerous Goods Transportation Based on Artificial Neural Network Algorithm
In order to improve the accuracy of the risk assessment of dangerous goods transportation in waterways,a particle optimization neural network method for risk assessment of waterway dangerous goods transportation is proposed.Firstly,the risk evaluation index of waterway dangerous goods transportation is selected by expert system,then the weight of evaluation index is determined by expert scoring method.Finally,the index weight is input into BP neural network for learning.BP neural network parameters are optimized by particle swarm optimization algorithm to obtain waterway dangerous goods transportation.Risk assessment level.The simulation results show that compared with the traditional waterway dangerous goods transportation risk assessment model,the particle optimization neural network accelerates the risk assessment of waterway dangerous goods transportation and improves the accuracy of waterway dangerous goods transportation risk assessment.
Waterway transportation particle swarm optimization BP neural network dangerous goods risk assessment
Wenge Cheng
Department of Maritime Technology,Tianjin Maritime College,China
国际会议
太原
英文
457-462
2019-06-29（万方平台首次上网日期，不代表论文的发表时间）