I am trying to make an estimation for the state-of-charge of a battery using the Feedforward Network. My inputs to the network are current, voltage and time. The network has 3 inputs (Voltage, Current and Time) with 1 Output (State-of-charge(SOC)). The network consists of 2 hidden layers with 10 neurons each and output layer with 1 neuron. Each Input has 54043 samples, so has the output.
I am training the network using the 'trainlm' and have set the performance goal to 1e-5. However, after training the network, the regression plot seems to have a R of 0.9999 in all the cases, which indicate to me that the network I am using is Overfitting the target.
Attched is the code and mat file containing the measurement data, any leads would be appreciated.
Below is the obtained regression plot:
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