IEEE

Locally Linear Continual Learning for Time Series based on VC-Theoretical Generalization Bounds

Abstract: Most machine learning methods assume fixed probability distributions, limiting their applicability in nonstationary real-world scenarios. While continual learning methods address this issue, ...
AZoBuild

Hybrid AI Model Improves Smart Building Energy Prediction

Net, a hybrid model that improves energy consumption prediction in low-energy buildings, enhancing accuracy and ...

Machine-learning method maps the uncertainty of biodiversity scenarios: The Bigfoot connection

To effectively protect biodiversity in an era of climate change, ecologists first have to know where animal and plant species ...
IEEE

A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence

Abstract: Power transformers are critical components in ensuring the continuous and stable operation of power systems. Failures in these units can lead to significant power outages and costly downtime ...