Solar is a significant renewable energy source. Solar energy can provide for the world's
energy needs while minimizing global warming from traditional sources. Forecasting the …

The accuracy of solar energy forecasting is critical for power system planning, management,
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …

Brain tumor classification is an expensive complicated challenge in the sector of clinical
image analysis. Machine learning algorithms enabled radiologists to accurately diagnose …

The growing threat of global climate change stemming from the huge carbon footprint left
behind by fossil fuels has prompted interest in exploring and utilizing renewable energy …

Industrial control systems (ICSs) are facing serious and evolving security threats because of
a variety of malicious attacks. Deep learning-based intrusion detection systems (IDSs) have …

Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …

Breast cancer is one of the most dangerous diseases for women's health, and it is imperative
to provide the necessary diagnostic assistance for it. The medical image processing …

With the continued growth of wind power penetration into conventional power grid systems,
wind power forecasting plays an increasingly competitive role in organizing and deploying …

Wind power forecasting is very crucial for power system planning and scheduling. Deep
neural networks (DNNs) are widely used in forecasting applications due to their exceptional …

Uncertain weather scenarios have an impact on the output of solar farms and therefore affect
the security of the grid. It is advantageous for power system operators to forecast solar …