Selling Icecreams: Difference between revisions

From Artificial Neural Network for PHP
 
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== FAQ ==

For information about dat-files have a view to the [[FAQ]] page.

== Training ==
== Training ==


<source lang="php">
<source lang="php">


require_once 'ANN/ANN_Network.php';
require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\InputValue;
use ANN\OutputValue;
use ANN\Values;


try
try
{
{
$network = ANN_Network::loadFromFile('icecreams.dat');
$objNetwork = Network::loadFromFile('icecreams.dat');
}
}
catch(Exception $e)
catch(Exception $e)
Line 13: Line 22:
print 'Creating a new one...';
print 'Creating a new one...';
$network = new ANN_Network(2,8,1);
$objNetwork = new Network(2, 5, 1);


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

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

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

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


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

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


$objValues = new Values;

$objValues->train()
->input(
$objTemperature->getInputValue(20),
$objHumidity->getInputValue(10)
)
->output(
$objIcecream->getOutputValue(20)
)
->input(
$objTemperature->getInputValue(30),
$objHumidity->getInputValue(40)
)
->output(
$objIcecream->getOutputValue(90)
)
->input(
$objTemperature->getInputValue(32),
$objHumidity->getInputValue(30)
)
->output(
$objIcecream->getOutputValue(70)
)
->input(
$objTemperature->getInputValue(33),
$objHumidity->getInputValue(20)
)
->output(
$objIcecream->getOutputValue(75)
);

$objValues->saveToFile('values_icecreams.dat');
unset($objValues);
unset($objTemperature);
unset($objHumidity);
unset($objIcecream);
}
}


try
$temperature = new ANN_InputValue(-15, 50); // Temperature
{
$objTemperature = InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius


$humidity = new ANN_InputValue(0, 100); // Humidity
$objHumidity = InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage


$objIcecream = OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
$icecream = new ANN_OutputValue(0, 300); // Ice-Creams
}
catch(Exception $e)
{
die('Error loading value objects');
}


try
$inputs = array(
{
array($temperature->getInputValue(20), $humidity->getInputValue(10)),
$objValues = Values::loadFromFile('values_icecreams.dat');
array($temperature->getInputValue(30), $humidity->getInputValue(40)),
}
array($temperature->getInputValue(32), $humidity->getInputValue(30)),
catch(Exception $e)
array($temperature->getInputValue(33), $humidity->getInputValue(20))
{
);
die('Loading of values failed');
}

$objNetwork->setValues($objValues); // to be called as of version 2.0.6

$boolTrained = $objNetwork->train();

print ($boolTrained)
? 'Network trained'
: 'Network not trained completely. Please re-run the script';

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

$objNetwork->printNetwork();
</source>

== Using trained network ==

<source lang="php">

require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\InputValue;
use ANN\OutputValue;
use ANN\Values;

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

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

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

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

try
{
$objValues = Values::loadFromFile('values_icecreams.dat');
}
catch(Exception $e)
{
die('Loading of values failed');
}


$objValues->input( // input values appending the loaded ones
$outputs = array(
$objTemperature->getInputValue(17),
array($icecream->getOutputValue(20)),
$objHumidity->getInputValue(12)
array($icecream->getOutputValue(90)),
)
array($icecream->getOutputValue(70)),
->input(
array($icecream->getOutputValue(75))
$objTemperature->getInputValue(31),
);
$objHumidity->getInputValue(42)
)
->input(
$objTemperature->getInputValue(31),
$objHumidity->getInputValue(34)
)
->input(
$objTemperature->getInputValue(34),
$objHumidity->getInputValue(21)
);


$objNetwork->setValues($objValues);
$network->setInputs($inputs);


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


foreach($arrOutputs as $arrOutput)
$network->train();
foreach($arrOutput as $floatOutput)
print $objIcecream->getRealOutputValue($floatOutput). '<br />';


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

Latest revision as of 11:33, 1 June 2011

FAQ

For information about dat-files have a view to the FAQ page.

Training

require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\InputValue;
use ANN\OutputValue;
use ANN\Values;

try
{
  $objNetwork = Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
  print 'Creating a new one...';
	
  $objNetwork = new Network(2, 5, 1);


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

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

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

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


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

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


  $objValues = new Values;

  $objValues->train()
            ->input(
                   $objTemperature->getInputValue(20),
                   $objHumidity->getInputValue(10)
                   )
            ->output(
                   $objIcecream->getOutputValue(20)
                   )
            ->input(
                   $objTemperature->getInputValue(30),
                   $objHumidity->getInputValue(40)
                   )
            ->output(
                   $objIcecream->getOutputValue(90)
                   )
            ->input(
                   $objTemperature->getInputValue(32),
                   $objHumidity->getInputValue(30)
                   )
            ->output(
                   $objIcecream->getOutputValue(70)
                   )
            ->input(
                   $objTemperature->getInputValue(33),
                   $objHumidity->getInputValue(20)
                   )
            ->output(
                   $objIcecream->getOutputValue(75)
                   );

  $objValues->saveToFile('values_icecreams.dat');
  
  unset($objValues);
  unset($objTemperature);
  unset($objHumidity);
  unset($objIcecream);
}

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

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

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

try
{
  $objValues = Values::loadFromFile('values_icecreams.dat');
}
catch(Exception $e)
{
  die('Loading of values failed');
}

$objNetwork->setValues($objValues); // to be called as of version 2.0.6

$boolTrained = $objNetwork->train();

print ($boolTrained)
        ? 'Network trained'
        : 'Network not trained completely. Please re-run the script';

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

$objNetwork->printNetwork();

Using trained network

require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\InputValue;
use ANN\OutputValue;
use ANN\Values;

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

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

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

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

try
{
  $objValues = Values::loadFromFile('values_icecreams.dat');
}
catch(Exception $e)
{
  die('Loading of values failed');
}

$objValues->input( // input values appending the loaded ones
                 $objTemperature->getInputValue(17),
                 $objHumidity->getInputValue(12)
                 )
          ->input(
                 $objTemperature->getInputValue(31),
                 $objHumidity->getInputValue(42)
                 )
          ->input(
                 $objTemperature->getInputValue(31),
                 $objHumidity->getInputValue(34)
                 )
          ->input(
                 $objTemperature->getInputValue(34),
                 $objHumidity->getInputValue(21)
                 );

$objNetwork->setValues($objValues);

$arrOutputs = $objNetwork->getOutputs();

foreach($arrOutputs as $arrOutput)
  foreach($arrOutput as $floatOutput)
    print $objIcecream->getRealOutputValue($floatOutput). '<br />';