Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial
interpolation problem to space and time dimensions. Here, we review the statistical, physical …

Nowadays, the buzzwords for organizations to be prepared for the competitive
environment's challenges are sustainability, digitalization, resilience and agility. However …

With the potential of Industry 4.0 technologies to enable sustainable manufacturing, asset
life cycle management (ALCM) has been gaining increasing attention in recent years. This …

Over the last decade, machine learning (ML) and deep learning (DL) algorithms have
significantly evolved and been employed in diverse applications, such as computer vision …

Choosing the appropriate deployment strategy for any Deep Learning (DL) project in a
production environment has always been the most challenging problem for industrial …

IoT and edge devices dedicated to run machine vision algorithms are usually few years
lagging currently available state-of-the-art technologies for hardware accelerators. This is …

The rapidly growing research landscape in finance, encompassing environmental, social,
and governance (ESG) topics and associated Artificial Intelligence (AI) applications …

Smart or intelligent built assets including infrastructure, buildings, real estate, and cities
provide enhanced functionality to their different users such as occupiers, passengers …

Feature Selection (FS) is a crucial step in high-dimensional and big data analytics. It
mitigates thecurse of dimensionality'by removing redundant and irrelevant features. Most FS …

Feature selection (FS) is a fundamental big data task, improving classification performance
by selecting a relevant feature subset to mitigate thecurse of dimensionality'. As the number …