Selling Icecreams: Difference between revisions

From Artificial Neural Network for PHP
Line 7: Line 7:
try
try
{
{
$network = ANN_Network::loadFromFile('icecreams.dat');
$objNetwork = ANN_Network::loadFromFile('icecreams.dat');
}
}
catch(Exception $e)
catch(Exception $e)
Line 13: Line 13:
print 'Creating a new one...';
print 'Creating a new one...';
$network = new ANN_Network(2,8,1);
$objNetwork = new ANN_Network(2, 8, 1);


$temperature = new ANN_InputValue(-15, 50); // Temperature in Celsius
$objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius


$temperature->saveToFile('input_temperature.dat');
$objTemperature->saveToFile('input_temperature.dat');
unset($temperature);
unset($objTemperature);


$humidity = new ANN_InputValue(0, 100); // Humidity percentage
$objHumidity = new ANN_InputValue(0, 100); // Humidity percentage


$humidity->saveToFile('input_humidity.dat');
$objHumidity->saveToFile('input_humidity.dat');


unset($humidity);
unset($objHumidity);


$icecream = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams
$objIcecream = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams


$icecream->saveToFile('output_quantity.dat');
$objIcecream->saveToFile('output_quantity.dat');


unset($icecream);
unset($objIcecream);
}
}


try
try
{
{
$temperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius
$objTemperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius


$humidity = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage
$objHumidity = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage


$icecream = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
$objIcecream = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
}
}
catch(Exception $e)
catch(Exception $e)
Line 47: Line 47:
}
}


$inputs = array(
$arrInputs = array(
array($temperature->getInputValue(20), $humidity->getInputValue(10)),
array($objTemperature->getInputValue(20), $objHumidity->getInputValue(10)),
array($temperature->getInputValue(30), $humidity->getInputValue(40)),
array($objTemperature->getInputValue(30), $objHumidity->getInputValue(40)),
array($temperature->getInputValue(32), $humidity->getInputValue(30)),
array($objTemperature->getInputValue(32), $objHumidity->getInputValue(30)),
array($temperature->getInputValue(33), $humidity->getInputValue(20))
array($objTemperature->getInputValue(33), $objHumidity->getInputValue(20))
);
);


$outputs = array(
$arrOutputs = array(
array($icecream->getOutputValue(20)),
array($objIcecream->getOutputValue(20)),
array($icecream->getOutputValue(90)),
array($objIcecream->getOutputValue(90)),
array($icecream->getOutputValue(70)),
array($objIcecream->getOutputValue(70)),
array($icecream->getOutputValue(75))
array($objIcecream->getOutputValue(75))
);
);


$network->setInputs($inputs);
$objNetwork->setInputs($arrInputs);


$network->setOutputs($outputs);
$objNetwork->setOutputs($arrOutputs);


$network->train();
$objNetwork->train();


$network->saveToFile('icecreams.dat');
$objNetwork->saveToFile('icecreams.dat');
</source>
</source>



Revision as of 12:47, 18 December 2008

Training

require_once 'ANN/ANN_Loader.php';

try
{
  $objNetwork = ANN_Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
  print 'Creating a new one...';
	
  $objNetwork = new ANN_Network(2, 8, 1);

  $objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius

  $objTemperature->saveToFile('input_temperature.dat');
  
  unset($objTemperature);

  $objHumidity    = new ANN_InputValue(0, 100);  // Humidity percentage

  $objHumidity->saveToFile('input_humidity.dat');

  unset($objHumidity);

  $objIcecream    = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams

  $objIcecream->saveToFile('output_quantity.dat');

  unset($objIcecream);
}

try
{
  $objTemperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius

  $objHumidity    = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage

  $objIcecream    = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
}
catch(Exception $e)
{
  print 'Error loading value objects';
}

$arrInputs = array(
		array($objTemperature->getInputValue(20), $objHumidity->getInputValue(10)),
		array($objTemperature->getInputValue(30), $objHumidity->getInputValue(40)),
		array($objTemperature->getInputValue(32), $objHumidity->getInputValue(30)),
		array($objTemperature->getInputValue(33), $objHumidity->getInputValue(20))
		);

$arrOutputs = array(
		array($objIcecream->getOutputValue(20)),
		array($objIcecream->getOutputValue(90)),
		array($objIcecream->getOutputValue(70)),
		array($objIcecream->getOutputValue(75))
		);

$objNetwork->setInputs($arrInputs);

$objNetwork->setOutputs($arrOutputs);

$objNetwork->train();

$objNetwork->saveToFile('icecreams.dat');

Using trained network

require_once 'ANN/ANN_Loader.php';

try
{
  $network = ANN_Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
  print 'Network not found.';
}

try
{
  $temperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius

  $humidity = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage

  $icecream = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
}
catch(Exception $e)
{
  print 'Error loading value objects';
}

$inputs = array(
	array($temperature->getInputValue(20), $humidity->getInputValue(10)),
	array($temperature->getInputValue(30), $humidity->getInputValue(40)),
	array($temperature->getInputValue(32), $humidity->getInputValue(30)),
	array($temperature->getInputValue(33), $humidity->getInputValue(20))
);

$network->setInputs($inputs);

$outputs = $network->getOutputs();

foreach($outputs as $output)
  print $icecream->getRealOutputValue($output). '<br />';