부산대학교 도서관

With the rapid development of computer technology, more and more people are starting to use computers in their daily lives and work. During aircraft flight, traditional aviation products require a lot of manpower and material resources to meet design requirements due to factors such as complex aircraft panel shapes, high precision requirements, and relatively dense structures. In order to save time and improve efficiency, this article utilizes research based on machine learning algorithms to optimize the layout of aircraft internal structures, including simplifying models, modifying geometric parameters, etc., in order to obtain more accurate analysis results. The test results show that the average accuracy of the system is around 0.95 plus or minus 0.02. By using the performance testing indicators and methods mentioned above, the performance of intelligent assembly optimization algorithms can be comprehensively evaluated for better application in practical problem solving.