Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …

Data mining is the discovery of interesting, unexpected or valuable structures in large
datasets. As such, it has two rather different aspects. One of these concerns large …

The only single-source——now completely updated and revised——to offer a unified
treatment of the theory, methodology, and applications of the EM algorithm Complete with …

Memristors are novel electrical devices used for a variety of applications, including memory,
logic circuits, and neuromorphic systems. Memristive technologies are attractive due to their …

The structure prediction at the atomic level is emerging as a state-of-the-art approach to
accelerate the functionality-driven discovery of materials. By combining the global swarm …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

We introduce the panel smooth transition regression model. This new model is intended for
characterizing heterogeneous panels, allowing the regression coefficients to vary both …

This new edition continues to serve as a comprehensive guide to modern and classical
methods of statistical computing. The book is comprised of four main parts spanning the …

This book is written for students and researchers in the field of industrial engineering,
computer science, operations research, management science, electrical engineering, and …

This paper presents a novel bio-inspired optimization algorithm called Coronavirus
Optimization Algorithm (COVIDOA). COVIDOA is an evolutionary search strategy that mimics …