Bestfitness matlab code using neural network

    clc;
    a= [39.8878 39.9947 39.9544 40.0285 39.9263 40.0013 40.9078 39.7623 40.9278];
    b=[0.6016 0.6016 0.6045 0.6074 0.6067 0.6074 0.6052 0.5998 0.6056] ;
    c=[100 100 100 100 100 100 100 100 100];
    y=a+ b.*c;
    I=[a; b; c];
    T=y;
    R=[0 1000; 0 1000 ; 0 1000];
    S=[5 1];
    net = newff([0 1000;0 1000 ;0 1000],[4 1],{'tansig','purelin'});
    O=[100.0439 100.5907 100.4028 100.7729 100.5963 100.7457 100.5964 99.7375 100.6877];
    net=train(net,I,O);
    O1=sim(net,I);
    plot(1:9,O,1:9,O1);
     net.IW{1}
     net.LW{2,1}
     BestFitness=sim(net,[39.8595 0.6023 100]');