Question
I am using nueral network to prdict the output of four inputs ( x1,...x4) I need to call the netowrk from another matlab file currently i am using save and load the net but this method takes time to load the net do you know any alternative method to call the net please. data=readmatrix( 'input.txt') x=data(:,1:4) y=data(:,5) m=length(y); Visulaisation of the data histogram(y,10) Normalise the features and transform the output y2=log(1+y) histogram(y2,10) plot(x(:,2),y2,'o') Normalise the input variables for i=1:4 x2(:,i)=(x(:,i)-min(x(:,i)))/(max(x(:,i))-min(x(:,i))) end Train an artificial neural network (ANN) rng default % For reproducibility xt=x2' yt=y2' hiddenLayerSize=16; net=fitnet(hiddenLayerSize) net.divideParam.trainratio=70/100; net.divideParam.valratio=30/100; net.divideParam.testratio=0/100; [net,tr]=train(net,xt,yt) performance of N.N yTrain=exp(net(xt(:,tr.trainInd)))-1 yTrainTrue=exp(yt(:,tr.trainInd))-1 sqrt(mean((yTrain-yTrainTrue).^2)) yVal=exp(net(xt(:,tr.valInd)))-1 yValTrue=exp(yt(:,tr.valInd))-1 sqrt(mean((yVal-yValTrue).^2)) gregnet1 = net; save gregnet1
Expert Answer
Prashant Kumar
PhD Expert
Answered Aug 15, 2026
You can use the sim function:
The sim function is usually called implicitly by calling the neural network as a function. For instance, these two expressions return the same result:
y = sim(net,x) y = net(x)
I think for your case, you need something like this:
% Read data
data = readmatrix("new_data.txt")
x=data(:,1:4)
y=data(:,5)
% Load saved network
load gregnet
net = gregnet1;
% Evaluate network on data
xt = x.';
yhat = exp(net(xt)-1).';
% Compare predictions with new data
ytrue = y;
sqrt(mean((yhat-yTrainTrue).^2))
If you want to use the sim function instead of net(xt), then replace the "yhat =" line with
yhat = exp( sim(net,xt) - 1).';
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