Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications

With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.

Key Topics Covered

• Introduces the theory underpinning hybrid swarm intelligence-enabled research as well as the leading applications across the fields of communication, networking, and information engineering
• Presents a range of applications research, including signal processing, communication engineering, bioinformatics, controllers, federated learning systems, blockchain, and IoT
• Includes case studies and code snippets in applications chapters