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we provided details on how to construct the individual terms of the loss function corresponding to the measurements, physical constraints and continuity, that the model should satisfy. In this section, we will show how to combine these individual terms to create the joint form of the loss function, together with some examples to clarify the procedure. The loss function of our physics informed neural networks (PINNs) takes the form:
This complete form of the loss function that encourages the model to learn the underlining physics of the problem by using measurements inside the domain, not necessarily at the boundaries and by respecting the imposed physical constraints.
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IEEE/ICACT20240208 Slide.08
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