lowernet.m

ANN基本知识和应用课件

Sample = [

 15,   15,   15,   15,   15,   15,   15,   15,   25,   25,   25,   25,   25,   25,   25,   25,   25,   25,   25,   35,   35,   35,   35,   35,   35,   35,   35,   35,   35,   35,   35,   35,   45,   45,   45,   45,   45,   45,   45,   45,   45,   45,   45,   45,   45,   45;

  5,    5,    5,    5,   15,   15,   15,   15,    5,    5,    5,    5,   15,   15,   15,   25,   25,   25,   25,    5,    5,    5,   15,   15,   15,   15,   25,   25,   25,   35,   35,   35,    5,    5,    5,    5,   15,   15,   15,   15,   25,   25,   25,   25,   35,   35;

0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  0.5,  1.0,  1.5,  2.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  2.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  0.5,  1.0,  1.5,  2.5,  1.5,  2.5

];

Target = [

3.85-61.9/15, 3.68-61.9/15, 3.52-61.9/15, 3.26-61.9/15, 4.05-61.9/15, 3.81-61.9/15, 3.69-61.9/15, 4.89-61.9/15, 2.37-61.9/25, 2.29-61.9/25, 2.23-61.9/25, 2.12-61.9/25, 2.40-61.9/25, 2.27-61.9/25, 2.16-61.9/25, 2.87-61.9/25, 2.41-61.9/25, 2.29-61.9/25, 2.12-61.9/25, 1.65-61.9/35, 1.61-61.9/35, 1.56-61.9/35, 1.69-61.9/35, 1.58-61.9/35, 1.54-61.9/35, 1.44-61.9/35, 1.81-61.9/35, 1.67-61.9/35, 1.41-61.9/35, 1.83-61.9/35, 1.67-61.9/35, 1.49-61.9/35, 1.32-61.9/45, 1.29-61.9/45, 1.28-61.9/45, 1.23-61.9/45, 4.61-61.9/45, 4.38-61.9/45, 4.21-61.9/45, 3.65-61.9/45, 1.38-61.9/45, 1.26-61.9/45, 1.18-61.9/45, 1.09-61.9/45, 1.23-61.9/45, 1.09-61.9/45

];

Test = [25,35,35,45;15,5,25,35;2.5,0.5,1.5,1.0];

Goal = [2.00,1.70,1.55,1.36];

Lower = network;

Lower.numInputs = 1;
Lower.numLayers = 3;

Lower.biasConnect = [1;1;1];
Lower.inputConnect = [1;0;0];
Lower.layerConnect = [0,0,0;1,0,0;0,1,0];
Lower.outputConnect = [0,0,1];
Lower.targetConnect = [0,0,1];

Lower.inputs{1}.size = 3;
Lower.inputs{1}.range = [15,45;5,35;0.5,2.5];

Lower.layers{1}.size = 5;
Lower.layers{1}.transferFcn = 'tansig';
Lower.layers{1}.initFcn = 'initnw';

Lower.layers{2}.size = 4;
Lower.layers{2}.transferFcn = 'tansig';
Lower.layers{2}.initFcn = 'initnw';

Lower.layers{3}.size = 1;
Lower.layers{3}.transferFcn = 'purelin';
Lower.layers{3}.initFcn = 'initnw';

Lower.initFcn = 'initlay';
Lower.performFcn = 'mse';
Lower.trainFcn = 'trainlm';

Lower.trainParam.epochs = 1e+6;
Lower.trainParam.goal = 5e-3;
Lower.trainParam.lr = 1e-3;

Lower = init(Lower);

Lower = train(Lower,Sample,Target);

Out = sim(Lower,Test)+[61.9/25,61.9/35,61.9/35,61.9/45];