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Digital transformation is reshaping business strategies and innovation, by creating new opportunities in different industries. Digital technologies, like eXtended Reality (XR) and Internet of Things (IoT), are rapidly advancing in the field of ...

Despite the recent increasing interest in digital pathology, efficient analysis of Whole Slide Images (WSIs) faces many challenges that hinder performance, such as their massive size, high heterogeneity, and imbalance distribution. This paper ...

Social media is a common medium for expression of views, discussion, sharing of content, and promotion of products and ideas. These views are either polite or obscene. The growth of hate speech is one of the negative aspects of the medium and its ...

In recent years, several population-based evolutionary and swarm algorithms have been developed and used in the literature. This work introduces an improved Cultural Algorithm with a modified selection function and a dynamic α-cognition procedure ...

• mCA-αC is an enhanced version of CAs with a modified selection function.
• CAs uses a dynamic α-cognition procedure that is proposed to introduce effective learning of the individuals though preserving the diversity of the population ...

Many real-life problems can be formulated as numerical optimization problems. Such problems pose a challenge for researchers when designing efficient techniques that are capable of finding the desired solution without suffering from premature ...

Antenna array synthesis problems are known to be nonlinear and non-convex optimization problems which require more robust optimization techniques than gradient-based techniques. This paper provides a comprehensive study of a class of evolutionary ...

Medical Imaging has become a vital technique that has been embraced in the diagnosis and treatment process of cancer. Histopathological slides, which microscopically examine the suspicious tissue, are considered the golden standard for tumor ...

Question Answering is a crucial natural language processing task. This field of research has attracted a sudden amount of interest lately due mainly to the integration of the deep learning models in the Question Answering Systems which ...

The recent advances in developing assistive devices have attracted researchers to use visual imagery (VI) mental tasks as a control paradigm to design brain–computer interfaces that can produce a large number of control signals. ...

• An EEG-based two-phase approach is proposed for decoding visually imagined objects.

Real-life problems can be expressed as optimization problems. These problems pose a challenge for researchers to design efficient algorithms that are capable of finding optimal solutions with the least budget. Stochastic Fractal Search (SFS) proved its ...

Hybridization in context to Evolutionary Computation (EC) strives to combine operators, components, and the best merits of different EC paradigms, to form a new evolutionary algorithm that enjoys a statistically superior performance, ...

Optimal active–reactive power dispatch problems (OARPD) are non-convex and highly nonlinear complex optimization problems. Typically, such problems are expensive in terms of computational time and cost due to the load variations over ...

• A new efficient differential evolution algorithm is propounded to solve OPF problems.

In smart grid, energy resource management is highly complex large-scale optimization problem where the aim is to maximize the incomes while minimizing operational costs. Due to presence of mixed-integer variables and non-linear constraints, recently the ...

Over the last few decades, many improved Evolutionary Algorithms (EAs) have been proposed to tackle different types of optimization problems. Genetic Algorithm (GA) among other canonical algorithms have not shown consistent performance over a range of ...

Developing efficient algorithms for solving multi-objective optimization problems is a challenging and essential task in many applications. This task involves two or more conflicting objectives that need to be simultaneously optimized. Many real-world ...

Solving real-world optimization problems is considered a challenging task. This is due to the variability of the characteristics in objective functions, the presence of enormous number of local optima within the search space and highly nonlinear ...

Many Differential Evolution algorithms are introduced in the literature to solve optimization problems with diverse set of characteristics. In this paper, we propose an extension of the previously published paper LSHADE-EpSin that was ranked as the joint ...

Multilevel inverters are mainly used for DC to AC power conversion and these inverters can be classified into types current source inverter (CSI) and voltage source inverter (VSI). Voltage source inverters are more common in power industry to convert ...

Many real-world problems can be formulated as optimization problems. Such problems pose a challenge for researchers in the design of efficient algorithms capable of finding the best solution with the least computational cost. In this paper, a new ...

The aim of hybridization in the context of evolutionary computation is to combine appropriate operators from different evolutionary computation paradigms to form a single technique that enjoys a statistically superior performance over a wide range of ...