Difference between revisions of "Selling Icecreams"

From Artificial Neural Network for PHP
Line 14: Line 14:
 
 
 
$network = new ANN_Network(2,8,1);
 
$network = new ANN_Network(2,8,1);
  +
 
$temperature = new ANN_InputValue(-15, 50); // Temperature in Celsius
  +
  +
$temperature->saveToFile('input_temperature.dat');
  +
  +
unset($temperature);
  +
  +
$humidity = new ANN_InputValue(0, 100); // Humidity percentage
  +
  +
$humidity->saveToFile('input_humidity.dat');
  +
  +
unset($humidity);
  +
  +
$icecream = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams
  +
  +
$icecream->saveToFile('output_quantity.dat');
  +
  +
unset($icecream);
 
}
 
}
   
  +
try
$temperature = new ANN_InputValue(-15, 50); // Temperature
 
  +
{
  +
$temperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius
   
$humidity = new ANN_InputValue(0, 100); // Humidity
+
$humidity = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage
   
$icecream = new ANN_OutputValue(0, 300); // Ice-Creams
+
$icecream = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
  +
}
  +
catch(Exception $e)
  +
{
  +
print 'Error loading value objects';
  +
}
   
 
$inputs = array(
 
$inputs = array(
Line 43: Line 68:
   
 
$network->saveToFile('icecreams.dat');
 
$network->saveToFile('icecreams.dat');
  +
</source>
  +
  +
== Using trained network ==
  +
  +
<source lang="php">
  +
  +
require_once 'ANN/ANN_Network.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 />';
  +
 
</source>
 
</source>

Revision as of 14:25, 31 December 2007

Training

require_once 'ANN/ANN_Network.php';

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

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

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

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

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

  unset($humidity);

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

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

  unset($icecream);
}

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))
);

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

$network->setInputs($inputs);

$network->setOutputs($outputs);

$network->train();

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

Using trained network

require_once 'ANN/ANN_Network.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 />';