The MetaInfrastructure group is pioneering the integration AI and ML into critical infrastructure protection, creating a foundation for rapid decision-making and enhancing resilience and energy efficiency in built ecosystems.
Prof. Ivan Izonin and Dr. Athanasia Kazantzi are on a winning streak, having recently published a series of impactful articles that advance this field. See below:
1. An approach toward improvement of ensemble method’s accuracy for data classification
read here: https://ijece.iaescore.com/index.php/IJECE/article/view/35701
2. A new method for Reducing Training Time ML-Based Cascade Scheme for Large-Volume Data Analysis
read here: https://www.mdpi.com/1424-8220/24/15/4762
3. Machine learning for predicting energy efficiency of buildings: A small data approach
read here: https://www.sciencedirect.com/science/article/pii/S1877050923021853
And perhaps the most interesting one in the journal Engineering with Computers titled:
4. GRNN-based cascade ensemble model for non-destructive damage state identification
read here: https://link.springer.com/article/10.1007/s00366-024-02048-1
