Predicting the dynamics of chaotic systems is one of the most challenging tasks for neural networks, and machine learning in general. Here we aim to predict the spatiotemporal chaotic dynamics of a high-dimensional non-linear system. In our attempt we use the TensorFlow library, representing the state of the art for deep neural networks training and prediction. While our results are encouraging, and show that the dynamics of the considered system can be predicted for short time, we also indirectly discovered an unexpected and undesirable behavior of the TensorFlow library. More specifically, the longer term prediction of the system's chaotic behavior quickly deteriorates and blows up due to the nondeterministic behavior of the TensorFlow library. Here we provide numerical evidence of the short time prediction ability, and of the longer term predictability blow up.

翻译：预测混沌系统的动力学是神经网络乃至机器学习领域最具挑战性的任务之一。本文旨在预测高维非线性系统的时空混沌动力学。我们采用当前深度神经网络训练与预测领域最先进的TensorFlow库。尽管研究结果表明，该系统的动力学可在短期内得到预测，但我们也间接发现了TensorFlow库的一种意外且非期望的行为。具体而言，系统混沌行为的长期预测会因TensorFlow库的非确定性行为而迅速恶化并产生数值爆炸。本文提供了短期预测能力及长期可预测性数值爆炸的数值证据。