Metaheuristic algorithms are widely known as efficient solutions for solving problems of
optimization. These algorithms supply powerful instruments with significant engineering …

Quantum computing (QC) is an emerging paradigm with the potential to offer significant
computational advantage over conventional classical computing by exploiting quantum …

Because of successful implementations and high intensity, metaheuristic research has been
extensively reported in literature, which covers algorithms, applications, comparisons, and …

Designing efficient and secure cryptosystems has been a preoccupation for many scientists
and engineers for a long time wherein they use chaotic systems to design new …

Membrane systems (also called P systems) refer to the computing models abstracted from
the structure and the functioning of the living cell as well as from the cooperation of cells in …

This article gives a survey of state-of-the-art methods for processing remotely sensed big
data and thoroughly investigates existing parallel implementations on diverse popular high …

The large data volume and high algorithm complexity of hyperspectral image (HSI) problems
have posed big challenges for efficient classification of massive HSI data repositories …

Quantum Computing is drawing a significant attention from the current scientific community.
The potential advantages offered by this revolutionary paradigm has led to an upsurge of …

An optimization spiking neural P system (OSNPS) aims to obtain the approximate solutions
of combinatorial optimization problems without the aid of evolutionary operators of …

This paper presents a new quantum chaotic cuckoo search algorithm (QCCS) for data
clustering. Recent researches show the superiority of cuckoo search (CS) over traditional …