The utilization of surrogate models to approximate complex systems has recently gained
increased popularity. Because of their capability to deal with black-box problems and lower …

Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …

Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

Business analytics aims to enable organizations to make quicker, better, and more
intelligent decisions with the aim to create business value. To date, the major focus in the …

Although scholars in management recognize the value of harnessing big data to
understand, predict and respond to future events, there remains little or very limited overview …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Heuristics are widely used for dealing with complex search and optimization problems.
However, manual design of heuristics can be often very labour extensive and requires rich …

Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It
has been widely tailored for a wide variety of optimization problems due to its impressive …

Background: Machine Learning (ML) is becoming increasingly popular in healthcare,
particularly for improving the timing and accuracy of diagnosis. ML can provide disease …