Is it possible with Neural Network

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John Doe
John Doe 2020-4-1
编辑： John Doe 2020-4-6
Hi everyone,
I hope you're safe and well.
I was wondering if it's possible to use Neural Network for the following:
I've calculated the volumes (my y) for every row in X, is it possible to use this data to train my network and to predict the volumes for every row in X1?
I'm trying to do this instead of having to do calculations for X1, or at least have a good representation?
I tried using this file here:
https://uk.mathworks.com/matlabcentral/fileexchange/64247-simple-neural-network
But kept getting an error.
Is what I'm thinking, even possible?
Any suggestions or insight would be helpful.
Thank you!
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Ameer Hamza
Ameer Hamza 2020-4-1
@John, do you have an explicit mathematical model that can relate the thickness values with the production? If yes, you can use curve fitting to model your system.
John Doe
John Doe 2020-4-1
@ Ameer, sadly it isn't explicit

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回答（1 个）

Ameer Hamza
Ameer Hamza 2020-4-1
If you have Deep learning toolbox, then you can do it in just in few lines of code
net = feedforwardnet([10 10]); % create a feedforward neural network with 2 hidden
% layers 10 neurons in each layer
net = train(net, X', y'); % train the neural network
y_predicted = net(X'); % calculate the prediction on training dataset
mean_square_error = mse(y_predicted, y'); % accuracy on training dataset
% make prediction on unknown dataset
Y1 = net(X1');
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John Doe
John Doe 2020-4-1
@Ameer, thank for trying to help! It's really appreciated.
I found this link:
https://stackoverflow.com/questions/21998987/programming-a-basic-neural-network-from-scratch-in-matlab
Do you think it'll help?
Ameer Hamza
Ameer Hamza 2020-4-1
I guess that can help, but it requires implementing the neural network from scratch. Even after that, I am sure the optimizer will fail for a medium-size neural network because, in that question, the OP used fminsearch, which does not have explicit information about gradient about the objective function. The neural network libraries usually calculate an analytical gradient of the whole network, which is why they can train the network so fast. Any other MATLAB optimizer will not have that information. Theoretically, you can provide that information yourself but calculating the gradient of your network, but that is a quite complex task.

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