Selling Icecreams
From Artificial Neural Network for PHP
FAQ
For information about dat-files have a view to the FAQ page.
Training
require_once 'ANN/Loader.php';
try
{
$objNetwork = ANN_Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
print 'Creating a new one...';
$objNetwork = new ANN_Network(2, 5, 1);
$objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius
$objTemperature->saveToFile('input_temperature.dat');
$objHumidity = new ANN_InputValue(0, 100); // Humidity percentage
$objHumidity->saveToFile('input_humidity.dat');
$objIcecream = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams
$objIcecream->saveToFile('output_quantity.dat');
$objValues = new ANN_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 = 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)
{
die('Error loading value objects');
}
try
{
$objValues = ANN_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';
try
{
$objNetwork = ANN_Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
die('Network not found');
}
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)
{
die('Error loading value objects');
}
try
{
$objValues = ANN_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 />';