[HTML][HTML] Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities
Despite widespread adoption and outstanding performance, machine learning models are
considered as “black boxes”, since it is very difficult to understand how such models operate …
considered as “black boxes”, since it is very difficult to understand how such models operate …
[HTML][HTML] Interpretable machine learning for building energy management: A state-of-the-art review
Abstract Machine learning has been widely adopted for improving building energy efficiency
and flexibility in the past decade owing to the ever-increasing availability of massive building …
and flexibility in the past decade owing to the ever-increasing availability of massive building …
A systematic review of explainable artificial intelligence in terms of different application domains and tasks
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …
and are now being employed in almost every application domain to develop automated or …
[HTML][HTML] Hybrid energy system integration and management for solar energy: A review
The conventional grid is increasingly integrating renewable energy sources like solar
energy to lower carbon emissions and other greenhouse gases. While energy management …
energy to lower carbon emissions and other greenhouse gases. While energy management …
An XAI approach for COVID-19 detection using transfer learning with X-ray images
Abstract The coronavirus disease (COVID-19) has continued to cause severe challenges
during this unprecedented time, affecting every part of daily life in terms of health …
during this unprecedented time, affecting every part of daily life in terms of health …
The enlightening role of explainable artificial intelligence in chronic wound classification
Artificial Intelligence (AI) has been among the most emerging research and industrial
application fields, especially in the healthcare domain, but operated as a black-box model …
application fields, especially in the healthcare domain, but operated as a black-box model …
Interpretable transformer model for capturing regime switching effects of real-time electricity prices
Real-time electricity prices are economic signals incentivizing market players to support real-
time system balancing. These price signals typically switch between low-and high-price …
time system balancing. These price signals typically switch between low-and high-price …
Neural network interpretability for forecasting of aggregated renewable generation
Y Lu, I Murzakhanov… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
With the rapid growth of renewable energy, lots of small photovoltaic (PV) prosumers
emerge. Due to the uncertainty of solar power generation, there is a need for aggregated …
emerge. Due to the uncertainty of solar power generation, there is a need for aggregated …
Interpretable uncertainty forecasting framework for robust configuration of energy storage in a virtual power plant
Q Wang, L Pan, Z Liu, H Wang, X Wang… - Journal of Energy …, 2024 - Elsevier
Accurate forecasting of load and renewable energy sources (RES) is crucial in the
configuration of an energy system. However, uncertainties of these variables present a …
configuration of an energy system. However, uncertainties of these variables present a …
Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
Examining the game-changing possibilities of explainable machine learning techniques, this
study explores the fast-growing area of biochar production prediction. The paper …
study explores the fast-growing area of biochar production prediction. The paper …