Neural networks: Calculating simple additions

Here's the complete code:

//

FANN_TEST.C:

FANN Test

//

Download the Fann library to the following Web site:

Fast Artificial Neural Network Library (Fann)

http://leenissen.dk/fann/

Download links: Download FANN---> C Source Code and Windows DLL files

//


#include ". /fann-2.0.0/src/include/doublefann.h "


#ifdef _DEBUG

#pragma comment (lib, "...). /fann-2.0.0/microsoftwindowsdll/bin/fanndoublemtd.lib ")

#else

#pragma comment (lib, "...). /fann-2.0.0/microsoftwindowsdll/bin/fanndoublemt.lib ")

#endif


Training:

Additive neural network

c = a+b;

void Train ()

{

const unsigned int num_input = 2; Number of items entered

const unsigned int num_output = 1; Number of output items

const unsigned int num_layers = 3;

const unsigned int num_neurons_hidden = 3;

const FLOAT Desired_error = (const float) 0.00000001;

const unsigned int max_epochs = 500000; Maximum execution times

const unsigned int epochs_between_reports = 10000; Reporting frequency


struct Fann *ann;


int Num = 200;

float Mf = num*3.f;

int i;

Double A, B, C;


FILE *FP;

Fopen_s (&FP, "Add.fann", "w");

fprintf_s (FP, "%d 2 1\n", Num);


Generate Training Files

For (I=1 i<=num; i++) {

Generates 2 numbers, required between (0,1)

A = I/MF;

b = (i+1)/mf;

c = a+b; Requirements between (0,1)


The input is written to the training file

fprintf_s (FP, "%lf%lf\n%lf\n", A, B, c);

}

Fclose (FP);


Sample Training

Ann = Fann_create_standard (num_layers, Num_input, Num_neurons_hidden, num_output);


Fann_set_activation_function_hidden (Ann, Fann_linear);

Fann_set_activation_function_output (Ann, Fann_linear);


Fann_train_on_file (Ann, "Add.fann", Max_epochs, Epochs_between_reports, Desired_error);

Fann_save (Ann, "Add.fann.net");

Fann_destroy (ANN);

}

Perform:

Test

void exec (double A, double b)

{

struct Fann *ann;


Fann_type *calc_out;

Fann_type input[2];

Ann = Fann_create_from_file ("add.fann.net");


Input[0] = A;

INPUT[1] = b;


Calc_out = Fann_run (ann, input);

Fann_destroy (ANN);

printf ("A=%f\nb=%f\nc=%f\n expected c=%f\n\n", input[0], input[1], calc_out[0], input[0]+input[1]);

}


//

Main program

//

int main ()

{

The following method only needs to be called once, then comment out

Train ();


EXEC (0.354,0.58934);

EXEC (0.21469,0.3914968);

EXEC (0.130,0.44);

EXEC ( -0.3654,0.58455);

EXEC (0.365420,-0.95);


return 0;

}