Implementation and certification of ML-based surrogate models in avionic systems

Key Points

• The research aims to evaluate the efficacy and compliance of ML-based surrogate models in legacy avionic systems.
• Assessment of surrogate models in the context of legacy systems
• Evaluation of implementability and certifiability standards
• Review of regulatory guidelines from EASA regarding ML applications
• Surrogate models are found to be provable and implementable in legacy systems
• Results indicate compliance with future EASA guidelines
• The potential for improved safety and efficiency in aviation applications is highlighted.