Neural Workflow Composer: Macro Execution via Neural Prediction

This case study demonstrates how Ascoos OS can intelligently execute macros based on system history using neural networks. The system learns from past performance metrics and predicts optimal macro actions.

Purpose

• Train a neural network with historical system data
• Predict whether a macro should be executed
• Execute macros based on prediction score

Core Ascoos OS Classes

• TNeuralNetworkHandler Neural network compilation, training, and prediction
• TMacroHandler Macro definition and execution logic

File Structure

The implementation resides in a single PHP file: - neural_workflow_composer.php

It contains all logic: data preparation, model training, prediction, and macro execution.

Requirements

1. PHP ? 8.2
2. Installed Ascoos OS or AWES 26

Execution Flow

1. Historical system data (CPU, RAM, Disk) is defined.
2. A neural network is compiled with two layers: - Input: 3 ? Hidden: 4 (ReLU) - Hidden: 4 ? Output: 1 (Sigmoid)
3. The model is trained with `fit()` using 1000 epochs and learning rate 0.01.
4. The current system state is evaluated.
5. If the prediction score > 0.5, a macro is executed.
6. Otherwise, macro execution is skipped.

Code Example

$composer = new TNeuralNetworkHandler();
$composer->compile([
    ['input' => 3, 'output' => 4, 'activation' => 'relu'],
    ['input' => 4, 'output' => 1, 'activation' => 'sigmoid']
]);
$composer->fit($systemData, $actions, epochs: 1000, lr: 0.01);

$score = $composer->predictNetwork([$currentState])[0];

if ($score > 0.5) {
    $macroHandler = new TMacroHandler();
    $macroHandler->addMacro(fn() => print("Executing optimized macro"), [], delay: 0, priority: 1);
    $macroHandler->runNext();
} else {
    print("Macro skipped based on neural prediction\n");
}

Expected Output

If the prediction score is high:

Executing optimized macro

Otherwise:

Macro skipped based on neural prediction

Resources

• Ascoos OS Documentation
• ASCOOS
• AWES
• GitHub Repository

Contribution

You can enhance the neural model, integrate additional system metrics, or extend macro logic. See CONTRIBUTING.md for guidelines.

License

This case study is covered under the Ascoos General License (AGL). See LICENSE.md.