Intelligent Algorithms Optimize the Level of Digital Engineering Quality Management

In view of the limitations of the traditional improved particle swarm optimization in the optimization of the quality management level of digital engineering, an optimization scheme of the quality management level based on intelligent algorithm was proposed. Firstly, the influencing factors is accurately located through AI theory, and the indicators is reasonably divided to reduce interference, and the intelligent algorithm is used to construct an optimization scheme for the quality management level. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional improved particle swarm optimization algorithm in terms of optimization accuracy and processing time of influencing factors at the quality management level, and has obvious advantages. The optimization of quality management level plays an extremely important role in the quality of digital engineering, which can accurately predict and optimize the growth characteristics and product generation of digital engineering quality. However, the traditional improved particle swarm optimization has certain limitations in solving the simulation problem of quality management, especially when dealing with complex problems. In this paper, this paper proposes an optimization scheme for quality management level based on intelligent algorithms to better solve this problem. The scheme accurately locates the influencing factors through AI theory, so as to determine the division of indicators, and uses intelligent algorithms to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on intelligent algorithm can better solve the limitations of the traditional improved particle swarm optimization and improve the simulation accuracy and efficiency in the optimization of digital engineering quality management.