can we use the ANN-GA optimisation algorithm to optimize chemical reactions?
if yes minimum how much data is required?
currently, I am working with a catalytic process I want to optimize the performance of the catalyst corresponding to the process parameters. previous research papers used from 32 to 48 process data. is it enough to predict and optimize the process parameters?
Please help me reg..this
You need to train a regression neural network with your experimental data. Then keep the trained neural network in your workspace. You can use this trained model as an objective function simply by using the function handle. Say the name of the trained model is 'trainednet'. The objective function can then be defined obj_func = predict(trainednet,x). You can use it as objective function by calling @obj_func
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