Software is increasingly vital, with automated systems regulating critical functions. As
development demands grow, manual code review becomes more challenging, often making …

This study explores crop yield forecasting through weight agnostic neural networks (WANN)
optimized by a modified metaheuristic. WANNs offer the potential for lighter networks with …

This study addresses the pressing issue of student dropout in higher education institutions
and explores the potential of artificial intelligence (AI) to mitigate this challenge. Student …

The scholarly exploration of employee satisfaction has intensified following the identification
of its correlation with work performance. Numerous intricate factors contribute significantly …

The simple recurrent artificial neural network is a deep artificial neural network frequently
used in the literature for solving forecasting problems. It is preferred due to its low number of …

The reduced costs associated with deploying and utilizing Unmanned Aerial Vehicles
(UAVs) have spurred their widespread adoption across various industries, including aerial …

Efforts in cardiovascular disorder detection demand immediate attention as they hold the
potential to revolutionize patient outcomes through early detection systems. The exploration …

Intense electromagnetic activity on the Sun's surface can lead to events known as solar
flares that often lead to mass ejections and other solar events. Sufficiently powerful solar …

This study explores the realm of time series forecasting, focusing on the utilization of
Recurrent Neural Networks (RNN) to detect abnormal cardiovascular rhythms in …

Machine learning as a subset of artificial intelligence presents a promising set of algorithms
for tackling increasingly complex challenges. A notable ability of this subgroup of algorithms …