Research on Data Integration and Algorithm Implementation of Intelligent Decision-Making Platform for Body Design - Lipeng, Qin; Shengqiang, Han; Jie, Zhao (IEEE International Conference on Artificial Intelligence and Computer Applications (Online), 2024)
This topic aims at the intelligentization and efficiency of automobile body design, and studies the data integration and algorithm implementation in automobile body design. The body design decision-making platform integrates multi-source information to build a complete body design information fusion system, so as to effectively circulate design data. This project intends to use the method of multi-source data fusion to study the precise transmission and application of body modeling data from three aspects: data preprocessing, feature extraction and model optimization. This paper constructs an intelligent decision-making algorithm, and test the accuracy and stability of the algorithm through simulation experiments. At the same time, the optimal body structure design scheme is given. Experiments have proved that the system can make fast and efficient decisions in different design environments. Finally, the practicality of the proposed method and method is verified through a detailed analysis of the simulation data. This provides a reference for the development of future intelligent decision-making platforms.