Deep Neural Network-Based High-Precision Identification of Weak Stability Boundary Structures
This paper proposes a deep neural network-based method that overcomes the limitations of conventional techniques by achieving both high computational efficiency and identification precision (97.26–99.91%) for weak stability boundary structures, thereby facilitating their application in ballistic capture analysis and low-energy transfer construction.