Proses Train

procedure fnProsesTrain;
var ii, jj, kk, nn, i, xx: integer;
    CT, Y2, net, D2, deltaB2, MSEchek, tempY2: Double;
    error, sumError, PE, sumPE, MAPE, aa, bb: Double;
    CP, Y1, D1, deltaW1, deltaW2, deltaB1, D1_net, tempNet: array of array of Double;
    Baris, Kolom: Word;
    themp: array of array of Double;
    jmlParam : Integer;
begin
  sTrain := True;
  sSave := False;
  try
    targetErr   := StrToFloatDef(FTrain.edTargetError.Text, 0.0000001);
    alfa        := StrToFloatDef(FTrain.edLearningRate.Text, 0);
    maxEpoch    := StrToIntDef(FTrain.edEpoch.Text, 0);
    kolTarget   := nodeInput + 1;

    fnSetBobot;

    sumError    := 0;
    MSEchek     := 1;
    Epoch       := 0;

    SetLength(MSE, 1, maxEpoch + 1);
    SetLength(Y2akhir, tLatih, 2);
    SetLength(tempArrYAkhir, tLatih, 2);

    TThread.Synchronize(nil, procedure begin
      FTrain.pbTrain.Max := maxEpoch;
      FTrain.pbTrain.Min := 0;
      FTrain.pbTrain.Value := 0;
      FTrain.tiPrintData.Enabled := True;
      FTrain.tiAutoSave.Enabled := True;
    end);

    while (Epoch < maxEpoch) do begin
      if (MSEchek > targetErr) then begin
        Inc(Epoch);
        errTrain := 0;
        for kk := 0 to tLatih - 1 do begin
          SetLength(CP, 1, nodeInput);
          for Kolom := 0 to nodeInput - 1 do
            CP[0, Kolom]:= DtLatihNorm[kk, Kolom];

          CT := DtLatihNorm[kk, kolTarget - 1];

          SetLength(themp, 1, nodeInput);
          SetLength(Y1, 1, nodeHidden);

          for ii:= 0 to nodeHidden - 1 do begin
            net:= 0;
            for kolom:= 0 to nodeInput - 1 do begin
              themp[0, Kolom] := CP[0, Kolom] * w1[ii, Kolom];
              net := net + themp[0, Kolom];
            end;

            net:= net + b1[ii, 0];
            Y1[0, ii] := Sigmoid(net);
          end;

          SetLength(themp, 1, nodeHidden);
          for ii:= 0 to nodeOutput - 1 do begin
            net:= 0;
            for Kolom := 0 to nodeHidden - 1 do begin
              themp[0, Kolom] := Y1[0, Kolom] * w2[ii, Kolom];
              net := net + themp[0, Kolom];
            end;
            net:= net + b2;
            Y2 := Sigmoid(net);
          end;

          Y2akhir[kk, 0] := CT;
          Y2akhir[kk, 1] := Y2;

          //menghitung error training
          error:= CT - Y2;

          //menghitung rata-rata error dari semua node per epoch
          sumError := sum(error);
          errTrain:= errTrain + sqr(sumError/1);

          //menghitung faktor koreksi pada tiap neuron di output    //turunan
          D2:= error * Y2 * (1 - Y2);  //sigmoid

          //menghitung delta w2
          SetLength(deltaW2, nodeOutput, nodeHidden);
          for jj:= 0 to nodeHidden-1 do begin
            for nn:= 0 to nodeOutput-1 do begin
              deltaW2[nn, jj]:= alfa * (D2 * Y1[0,jj]);
            end;
          end;

          //menghitung delta b2
          for nn:= 0 to nodeOutput-1 do begin
            deltaB2:= alfa * D2;
          end;

          //menghitung faktor koreksi pada tiap neuron di hidden
          SetLength(D1_net, 1, nodeHidden);
          SetLength(D1, 1, nodeHidden);
          for jj:= 0 to nodeHidden-1 do begin
            D1_net[0, jj]:= D2 * w2[0,jj];
          end;

          for Kolom:= 0 to nodeHidden-1 do                   //turunan
            D1[0, kolom]:= D1_net[0, Kolom] * Y1[0, Kolom] * (1-Y1[0, Kolom]);

          //menghitung delta w1
          SetLength(deltaW1, nodeHidden, nodeInput);
          for jj:= 0 to nodeInput-1 do begin
            for nn:=0 to nodeHidden-1 do begin
              deltaW1[nn, jj]:= alfa * (D1[0, nn] * CP[0, jj]);
            end;
          end;

          //menghitung delta b1
          SetLength(deltaB1, nodeHidden, 1);
          for nn:= 0 to nodeHidden-1 do begin
            deltaB1[nn, 0] := alfa * D1[0, nn];
          end;

          //update semua bobot dan bias
          for Baris:= 0 to nodeHidden-1 do
            for Kolom:= 0 to nodeInput-1 do
              w1[Baris, Kolom] := w1[Baris, Kolom] + deltaW1[Baris, Kolom];

          for Baris:= 0 to nodeOutput-1 do
            for Kolom:= 0 to nodeHidden-1 do
              w2[Baris, Kolom] := w2[Baris, Kolom] + deltaW2[Baris, Kolom];

          for Baris:= 0 to nodeHidden-1 do
            for Kolom:= 0 to nodeOutput-1 do
              b1[Baris, Kolom] := b1[Baris, Kolom] + deltaB1[Baris, Kolom];

          b2:= b2 + deltaB2;
        end;

        //SetLength(MSE, 1, maxEpoch + 1);
        MSE[0, Epoch-1]:= (errTrain / tLatih);
        MSEchek:= errTrain / tLatih;
        MSEterakhir:= MSE[0, Epoch-1];

        if sAutoSave then
          fnSimpanParameter;

        if not sTrain then
          Break;

      end else begin
        Break;
      end;
    end;
  finally
    sTrain := False;
    TThread.Synchronize(nil, procedure begin
      fnHasilTrain;
      fnProsesTest;
      fnHasilTest;

      if FTrain.cbSimpanBerkala.IsChecked then
        fnSimpanParameter;

      FTrain.btnSimpan.Enabled := True;
      FTrain.btnProses.Enabled := True;
      FTrain.btnProsesData.Enabled := True;
      FTrain.fnSetEnabledInput(True);
      FTrain.tiPrintData.Enabled := False;
      FTrain.tiAutoSave.Enabled := False;

      FTrain.pbTrain.Value := Epoch;
      FTrain.lblEpoch.Text := Epoch.ToString + ' / ' + maxEpoch.ToString;
    end);
  end;
end;