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">
<?php
require_once '../ANN/Loader.php';


use ANN\Network;
require_once 'ANN/ANN_Network.php';
use ANN\InputValue;
use ANN\OutputValue;
use ANN\Values;


try
try {
$objNetwork = Network::loadFromFile('icecreams.dat');
{
} catch (Exception $e) {
$network = ANN_Network::loadFromFile('icecreams.dat');
$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');
}
}

catch(Exception $e)
try {
{
$objValues = Values::loadFromFile('values_icecreams.dat');
print 'Creating a new one...';
} catch (Exception $e) {
die('Loading of values failed');
$network = new ANN_Network(2,8,1);
}
}


$objNetwork->setValues($objValues);
$temperature = new ANN_InputValue(-15, 50); // Temperature


$boolTrained = $objNetwork->train();
$humidity = new ANN_InputValue(0, 100); // Humidity


print ($boolTrained) ? 'Network trained' : 'Network not trained completely. Please re-run the script';
$icecream = new ANN_OutputValue(0, 300); // Ice-Creams


$objNetwork->saveToFile('icecreams.dat');
$inputs = array(
</source>
array($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))
);


== Using trained network ==
$outputs = array(

array($icecream->getOutputValue(20)),
<source lang="php">
array($icecream->getOutputValue(90)),
<?php
array($icecream->getOutputValue(70)),
require_once '../ANN/Loader.php';
array($icecream->getOutputValue(75))

);
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
$network->setInputs($inputs);
$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);
$network->setOutputs($outputs);


$arrOutputs = $objNetwork->getOutputs();
$network->train();


foreach ($arrOutputs as $arrOutput)
$network->saveToFile('icecreams.dat');
foreach ($arrOutput as $floatOutput)
print $objIcecream->getRealOutputValue($floatOutput) . "\n";
</source>
</source>

Latest revision as of 07:59, 6 October 2025

FAQ

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

Training

<?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) {
    $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');
}

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

$objNetwork->setValues($objValues);

$boolTrained = $objNetwork->train();

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

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

Using trained network

<?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
$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) . "\n";