Exploration of Sustainable Excellent Engineer Cultivation Path Based on Intelligent Augmentation

Regarding the problems in the training of engineers in Chinese universities, such as insufficient personalized training methods for different students, the effectiveness of student training needs to be pursued for excellence, sustainable personnel training path needs to be continuously improved, an original path for sustainable excellent engineer cultivation is proposed on the basis of intelligent augmentation (IA) in this paper. Firstly, in order to achieve friendly “human-machine coexistence”, a novel excellent engineer cultivation IA interaction framework is designed. Then, the modelling of IA-based engineers training is expressed by fitting with three methods based on Matlab software. Next, IA-based excellent engineer cultivation strategy is obtained by different optimization algorithms, such as sparrow search algorithm (SSA), particle swarm optimization algorithm (PSO), and human evolutionary optimization algorithm (HEOA), so to provide users with personalized training strategies based on their individual needs. After that, an IA-based sustainable excellent engineer cultivation measure is given. Finally, by the case analysis on students from Nanjing University of Aeronautics and Astronautics, the feasibility and effect of the proposed path for sustainable excellent engineer cultivation is verified effectively.