Construction of Crew Education and Training Quality Evaluation System and Its Impact on Shipping Safety

Abstract

Nowadays, shipping safety accidents occur frequently, and crew education and training can reduce the occurrence of shipping accidents to a certain extent, but there is no way to explore the specific relationship between crew education and training and shipping safety. There is no way to investigate. To solve the problem, the research uses the Genetic algorithm (GA) to optimize the Back propagation (BP) algorithm to obtain the Genetic Algorithm-Back propagation (GA-BP) algorithm, and the crew The relevant indicators in education and training are input into the algorithm to predict the safety of shipping. The performance comparison experiments of GA-BP and particle swarm optimization-back propagation Algorithm particle swarm optimization-Back propagation (APSO-BP) algorithm and traditional BP algorithm are carried out. The experimental outcomes show that the hit rate of GA-BP is 90%, and its average absolute errors are 0.00152, which are better than APSO-BP and traditional BP algorithms. In addition, in the empirical analysis of the model, it is found that the output outcomes of psychological quality and resilience are 0.92 and 0.93, respectively. The above outcomes show that the optimized GA-BP has better predictive performance, and the specific effects of psychological quality and resilience in crew education and training on the safety of shipping can be obtained. This method not only provides data support for the improvement of crew education and training methods, but also provides a new method for the safety prediction of shipping.