How I can Pass The same training, validation and test data to different neural nets?

I want to train two networks with the taining, validation and testing data

I'm trying to overwrite net.divideParam.trainInd, net.divideParam.valInd, net.divideParam.testInd

I have the following error: 'trainInd' is not a legal parameter.

Data = load('Data.txt');
Train = num2cell(Data');
Delay = 4; Neurons = 20;
trainRatio = 0.8; valRatio = 0.10; testRatio = 0.10;
[trainInd,valInd,testInd] = dividerand(length(Data),trainRatio,valRatio,testRatio);
%======================
%        NAR 1
%======================
net1 = narnet(1:Delay,Neurons);
X1 = Train;
[Xs1,Xi1,Ai1,Ts1] = preparets(net1,{},{},X1);
net1.divideParam.trainInd = trainInd; 
net1.divideParam.valInd = valInd; 
net1.divideParam.testInd = testInd;
net1 = train(net1,Xs1,Ts1,Xi1,Ai1);
%======================
%        NAR 2
%======================
net2 = narnet(1:Delay,Neurons);
X2 = Train;
[Xs2,Xi2,Ai2,Ts2] = preparets(net2,{},{},X2);
net2.divideParam.trainInd = trainInd; 
net2.divideParam.valInd = valInd; 
net2.divideParam.testInd = testInd;
net2 = train(net2,Xs2,Ts2,Xi2,Ai2);

Answer 1

[Muhammad Saafan]

I found some way by fixing the random seed in the following link.

Is there another way?

https://stackoverflow.com/questions/38475330/why-do-i-get-different-neural-network-training-results-each-time-even-the-initia