How to change the activation function in ANN model created using toolbox
I've created this model by editing the codes from the toolbox. The purpose of this model is to train the network with operating data from a turbine. the data is normalized and then the target will be set according to the actual fault occurrence which tagged as "1" and during normal operation "0". I will be comparing the result of several training function, the number of neuron, the number of layers, and activation function. % This script assumes these variables are defined: % data - input data. % target - target data. % load data load data.mat; load target.mat; x = data; t = target; % Choose a Training Function % For a list of all training functions type: help nntrain % 'trainlm' is usually fastest. % 'trainbr' takes longer but may be better for challenging problems. % 'trainscg' uses less memory. NFTOOL falls back to this in low memory situations. trainFcn = 'trainbr'; % Bayesian Regularization % Create a Feedforward Network hiddenLayerSize = 18; net = feedforwardnet (hiddenLayerSize,trainFcn); % Setup Division of Data for Training, Validation, Testing RandStream.setGlobalStream(RandStream('mt19937ar','seed',1)); % to get constant result net.divideFcn = 'divideblock'; % Divide targets into three sets using blocks of indices net.divideParam.trainRatio = 70/100; net.divideParam.valRatio = 15/100; net.divideParam.testRatio = 15/100; %TRAINING PARAMETERS net.trainParam.show=50; %# of ephocs in display net.trainParam.lr=0.05; %learning rate net.trainParam.epochs=10000; %max epochs net.trainParam.goal=0.05^2; %training goal net.performFcn='mse'; %Name of a network performance function %type help nnperformance % Train the Network [net,tr] = train(net,x,t); % Test the Network y = net(x); e = gsubtract(t,y); performance = perform(net,t,y) % View the Network view(net) The questions are: Is it correct to use this code below and will it affect the function of my model? RandStream.setGlobalStream(RandStream('mt19937ar','seed',1)); % to get constant result How to add another hidden layer? How to change the activation function for each layer? What is the best plot to show the capability of the ANN model to detect the fault of the turbine earlier than existing control system. Please advise me if there are anything that can be corrected/improved.
Kshitij Singh answered .
2025-11-20
1. Use FITNET (calls FEEDFORWARDNET) for regression and curve-fitting
2. Use PATTERNNET (calls FEEDFORWARDNET) for classification and pattern-recognition
3. You have a classification problem. Start with the simple code in
help patternnet
doc patternnet
4. If there are c classes, the target matrix columns should be columns of eye(c): O = c.
5. The relationship between trueclass indices 1:c and the target columns is
target = ind2vec(trueclassindices);
trueclassindices = vec2ind(target);
6. Before starting the design, get a "feel" for the data. This may include
a. plot inputs
b. plot targets
c. plot targets vs inputs
d. standardize inputs to zero mean and unit variance using zscore or mapstd.
e. Repeat a and c
f. Remove or modify errors and outliers.
7. Start simple with the example used in the help and doc documentation.
help patternnet
doc patternnet
8. You only have to vary 2 things
a. Number of hidden nodes (want as small as feasible)
b. Initial random weights
9. This can be accomplished with a double for loop as I have illustrated in zillions of examples in the NEWSGROUP and ANSWERS. Search results
NEWSGROUP HITS
greg patternnet Ntrials 8
ANSWERS HITS
greg patternnet Ntrials 60
greg patternnet Ntrials Hmax 22
greg patternnet Ntrials Hub 17
greg patternnet Ntrials Hub Hmax 10