神经网络lazarus代码例子

好的，下面是使用 Lazarus 和 Free Pascal 实现的简单神经网络的例子：

uses
  Math;

const
  NumInputs = 2;
  NumHidden = 3;
  NumOutputs = 1;

type
  TNeuralNet = class
  private
    FInputs: array[0..NumInputs-1] of Single;
    FHidden: array[0..NumHidden-1] of Single;
    FOutput: array[0..NumOutputs-1] of Single;
    FWeightsIH: array[0..NumInputs-1, 0..NumHidden-1] of Single;
    FWeightsHO: array[0..NumHidden-1, 0..NumOutputs-1] of Single;
  public
    constructor Create;
    procedure InitializeWeights;
    procedure ComputeOutput(Inputs: array of Single);
    property Output: array[0..NumOutputs-1] of Single read FOutput;
  end;

constructor TNeuralNet.Create;
begin
  InitializeWeights;
end;

procedure TNeuralNet.InitializeWeights;
var
  I, J: Integer;
begin
  Randomize;
  for I := 0 to NumInputs-1 do
    for J := 0 to NumHidden-1 do
      FWeightsIH[I, J] := Random;
  for I := 0 to NumHidden-1 do
    for J := 0 to NumOutputs-1 do
      FWeightsHO[I, J] := Random;
end;

procedure TNeuralNet.ComputeOutput(Inputs: array of Single);
var
  I, J: Integer;
begin
  for I := 0 to NumInputs-1 do
    FInputs[I] := Inputs[I];
  for I := 0 to NumHidden-1 do
  begin
    FHidden[I] := 0;
    for J := 0 to NumInputs-1 do
      FHidden[I] := FHidden[I] + FInputs[J] * FWeightsIH[J, I];
    FHidden[I] := 1 / (1 + Exp(-FHidden[I]));
  end;
  for I := 0 to NumOutputs-1 do
  begin
    FOutput[I] := 0;
    for J := 0 to NumHidden-1 do
      FOutput[I] := FOutput[I] + FHidden[J] * FWeightsHO[J, I];
    FOutput[I] := 1 / (1 + Exp(-FOutput[I]));
  end;
end;

var
  NeuralNet: TNeuralNet;
  Inputs: array[0..NumInputs-1] of Single;
  Output: Single;
begin
  NeuralNet := TNeuralNet.Create;
  Inputs[0] := 1;
  Inputs[1] := 1;
  NeuralNet.ComputeOutput(Inputs);
  Output := NeuralNet.Output[0];
  WriteLn(Output);
end.

在这