Human Error Evaluation Model of Civil Aviation Maintenance Based on Grey Wolf Optimizer

Abstract

Today, with the rapid development of science and technology, human error has already surpassed mechanical failure and become the most important factor in safety accidents. In order to reduce the occurrence of human error in civil aviation maintenance, and to improve the quality of maintenance production, four levels and 18 factors affecting human error in civil aviation maintenance are proposed in this paper,Taking Hongqiao base of Eastern Airlines as an example, a questionnaire survey was used to collect data,and an Inertial Adaptive Hybrid Gray Wolf Optimization (IAHGWO) was proposed,which combined with particle swarm optimization (PSO) and three improved strategies,and an evaluation model was constructed to use IAHGWO to train BP neural network. The results show that the evaluation model has good practicability and accuracy.