Deep Learning-based Analysis of Basins of Attraction

This study showcases the effectiveness of convolutional neural networks (CNNs) in characterizing the complexity and unpredictability of basins of attraction for diverse dynamical systems. This novel method is optimal for exploring different parameters of dynamical systems since the conventional methods are computationally expensive for characterizing multiple basins of attraction. Additionally, our research includes a comparison of different CNN architectures for this task showing the superiority of our proposed characterization method over the conventional methods, even with obsolete architectures.