We can use different measurements and data-driven approaches, such as machine learning methods in understanding and solving dynamical systems. Often, we already have some prior knowledge about the problem at hand, which we can incorporate into the machine learning process in several different ways. Using the example of balancing of rigid rotors, we will look at several possible ways of introducing prior knowledge to predict the location and mass needed to reduce mass imbalance. With the help of the TensorFlow library, we will create multiple models and evaluate them based on defined criteria.
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