Research on Intelligent Selection Algorithm of Aerospace Components based on Big Data

Traditional aerospace component selection methods based on the technology inheritance and application history can no longer meet the increasingly complex spacecraft development missions. An intelligent selection algorithm of aerospace components is proposed in this paper. In order to adapt to different functional application scenarios, advanced methods such as statistical analysis, collaborative filtering algorithm, content association algorithm, classification and clustering algorithm and deep neural network should be studied. These advanced methods should be combined with the prior knowledge and selection experience accumulated during spacecraft development for many years. With the help of digital and network selection platform, to achieve intelligent and diversified selection of components selection can be achieved. The proposed method can assist designers to select more and apply components accurately and efficiently, and improve the robustness and reliability of spacecraft single design.