This is my first post. In electrochemistry, complex impedance data is modelled using equivalent circuit models. This is based on non-linear least squares fitting of data comprising of real and imaginary complex function. Typical plot recorded at different conditions is attached. I wish to know if TensorFlow could be used to model such experimental data keeping in mind the actual electrochemical processes occurring in the system, which is a pre-condition for selecting an equivalent circuit model. Input is real impedance and complex impedance and the output should be the fitted data. In general, I wish to know if multiple sets of data (as shown in the image) can be simultaneously fitted using a single ANN model as ir pertains to a single system but under different conditions. The plot shown is at a particular temperature (773 K). I can add data sets recorded at other temperatures as well so that we can have a generalized ANN model for a specific system. Is it possible?
