Quo vadis artificial intelligence?
The study of artificial intelligence (AI) has been a continuous endeavor of scientists and
engineers for over 65 years. The simple contention is that human-created machines can do …
engineers for over 65 years. The simple contention is that human-created machines can do …
Artificial intelligence applied to battery research: hype or reality?
T Lombardo, M Duquesnoy, H El-Bouysidy… - Chemical …, 2021 - ACS Publications
This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …
potential to change our energy supply, trade, and consumption dramatically. The new …
[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …
resulted in increased energy demand. Since energy resources are scarce and should be …
A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
Review on deep learning applications in frequency analysis and control of modern power system
The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …
regional power grids in wide area and large scale have led the modern power system to …
An experimental review on deep learning architectures for time series forecasting
P Lara-Benítez, M Carranza-García… - International journal of …, 2021 - World Scientific
In recent years, deep learning techniques have outperformed traditional models in many
machine learning tasks. Deep neural networks have successfully been applied to address …
machine learning tasks. Deep neural networks have successfully been applied to address …
Prediction of solar energy guided by pearson correlation using machine learning
I Jebli, FZ Belouadha, MI Kabbaj, A Tilioua - Energy, 2021 - Elsevier
Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy market and reducing the dependence on fossil fuels in economic …
power plants in the energy market and reducing the dependence on fossil fuels in economic …
Integration of smart grid with renewable energy sources: Opportunities and challenges–A comprehensive review
Renewable energy is the most promising solution to the rising problem of greenhouse gas
emissions, and it also contributes to environmental protection. A typical electrical grid is a …
emissions, and it also contributes to environmental protection. A typical electrical grid is a …
Applications of IoT for optimized greenhouse environment and resources management
The role of Internet-of-Things (IoT) in precision agriculture and smart greenhouses has been
reinforced by recent R&D projects, growing commercialization of IoT infrastructure, and …
reinforced by recent R&D projects, growing commercialization of IoT infrastructure, and …