Class MLIntegrationExamples

java.lang.Object

neqsim.process.safety.risk.ml.MLIntegrationExamples

public class MLIntegrationExamples
extends Object

Examples and templates for integrating external ML frameworks with the risk system.

This class provides patterns and examples for integrating machine learning models from external frameworks like TensorFlow, PyTorch, ONNX, and scikit-learn with the NeqSim risk framework.

Supported Integration Patterns

• ONNX Runtime - Platform-independent ML model execution
• TensorFlow Java API - Direct TensorFlow model loading
• Deep Java Library (DJL) - Unified API for multiple backends
• REST API - External model serving endpoints

Usage Example

// Create adapter for external model
MLModelAdapter adapter =
    MLIntegrationExamples.createOnnxAdapter("/models/failure_predictor.onnx");

// Register with risk interface
RiskMLInterface mlInterface = new RiskMLInterface();
mlInterface.registerModel("failure_predictor", RiskMLInterface.ModelType.FAILURE_PREDICTION,
    adapter::predict);

Since:

3.3.0

Version:

1.0

Author:

NeqSim Development Team

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	MLIntegrationExamples.BaseMLAdapter	Base adapter class with common functionality.
static interface	MLIntegrationExamples.MLModelAdapter	Interface for ML model adapters.
static class	MLIntegrationExamples.OnnxAdapter	Adapter for ONNX Runtime models.
static class	MLIntegrationExamples.RestApiAdapter	Adapter for REST API-based model serving.
static class	MLIntegrationExamples.TensorFlowAdapter	Adapter for TensorFlow SavedModel format.
static class	MLIntegrationExamples.ThresholdModel	Simple threshold-based model for testing and fallback.

Field Summary

Fields

Modifier and Type	Field	Description
private static final org.apache.logging.log4j.Logger	logger

Constructor Summary

Constructors

Constructor	Description
MLIntegrationExamples()

Method Summary

Modifier and Type	Method	Description
static MLIntegrationExamples.OnnxAdapter	createOnnxFailurePredictor(String modelPath)	Creates an ONNX adapter for failure prediction.
static MLIntegrationExamples.RestApiAdapter	createRestAnomalyDetector(String endpoint)	Creates a REST API adapter for anomaly detection.
static MLIntegrationExamples.ThresholdModel	createTestAnomalyDetector()	Creates a simple threshold-based anomaly detector for testing.
static MLIntegrationExamples.ThresholdModel	createTestFailurePredictor()	Creates a simple threshold-based failure predictor for testing.
static void	main(String[] args)	Demonstrates integration with RiskMLInterface.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

logger

private static final org.apache.logging.log4j.Logger logger

Constructor Details

MLIntegrationExamples

public MLIntegrationExamples()

Method Details

createOnnxFailurePredictor

public static MLIntegrationExamples.OnnxAdapter createOnnxFailurePredictor(String modelPath)

Creates an ONNX adapter for failure prediction.

Parameters:

modelPath - path to ONNX model

Returns:

configured adapter

createRestAnomalyDetector

public static MLIntegrationExamples.RestApiAdapter createRestAnomalyDetector(String endpoint)

Creates a REST API adapter for anomaly detection.

Parameters:

endpoint - model serving endpoint

Returns:

configured adapter

createTestFailurePredictor

public static MLIntegrationExamples.ThresholdModel createTestFailurePredictor()

Creates a simple threshold-based failure predictor for testing.

Returns:

threshold model

createTestAnomalyDetector

public static MLIntegrationExamples.ThresholdModel createTestAnomalyDetector()

Creates a simple threshold-based anomaly detector for testing.

Returns:

threshold model

main

public static void main(String[] args)

Demonstrates integration with RiskMLInterface.

Parameters:

args - command line arguments