Research on the Algorithm of Artificial Intelligence in Ship Structure Optimization Design

This project intends to use a method combining particle swarm optimization (PSO) and differential evolution (DE) to perform overall optimization of ship structures. The good global optimization performance of particle swarms and the local optimization function of evolutionary algorithms are combined to overcome the local extreme value problem of a single particle swarm. In order to test the effectiveness of this method, a new improved method is proposed, which is developed according to the needs of a specific project. Experiments have shown that this method has good convergence and accuracy. Through an example analysis of a typical hull structure, the results show that this method can improve the hull strength by 5.8%, while reducing the required material consumption by 3.4%. The method proposed in this project can not only effectively improve the overall characteristics of the hull, but also has a good calculation effect, which can provide strong technical support for the development of ships.