Background: As Machine Learning (ML) advances rapidly in many fields, it is being adopted
by academics and businesses alike. However, ML has a number of different challenges in …

In today's technology-driven environment, the exponential growth of big data underscores
the importance of visualizing and analyzing it to derive actionable insights. This need spans …

Due to the ever increasing amount of data that is produced and captured in today's world,
the concept of big data has risen to prominence. However, implementing the respective …

Undoubtedly, the increase of available data and competitive machine learning algorithms
has boosted the popularity of data-driven modeling in energy systems. Applications are …

Achieving net-zero carbon emissions necessitates the major transformation of electrical
grids into smart grids. In this context, urban districts play a crucial role in the flexible …

For a given specific machine learning task, very often several machine learning algorithms
and their right configurations are tested in a trial-and-error approach, until an adequate …

With the rapid development of artificial intelligence, the selection of algorithms that meet
application requirements from feasible algorithms has become a critical problem to be …

With the growth of online banking, there has been a rise in identity theft and other
cybercrimes. What is missing in the current published literature is how historical identity theft …

With the continuous growth of business volume and functional requirements, the application
of major business systems is gradually implementing the upgrade from the Spring Boot …