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Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications
Siddhartha Bhattacharyya,Mario Köppen,Debashis De,Bijaya Ketan Panigrahi
- 415 pages
- English
- ePUB (mobile friendly)
- Only available on web
Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications
Siddhartha Bhattacharyya,Mario Köppen,Debashis De,Bijaya Ketan Panigrahi
About This Book
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.
Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on the recent and most up-to-date technologies combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. 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.
- 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
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Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- Preface
- Chapter 1 Emerging trends in computational swarm intelligence: A comprehensive overview
- Chapter 2 Innovative intelligent systems and applications: A Swarm intelligence perspective
- Chapter 3 Medical image analysis using swarm intelligence: A survey
- Chapter 4 An optimal and robust segmentation framework for analysis and detection of brain tumor in MRI images
- Chapter 5 Autoimmune diseases and an approach to type 1 diabetes analysis using PSO, K-means, and silhouette values
- Chapter 6 Consumer portfolio management with usage of evolutionary approach by PSO algorithm and machine learning models
- Chapter 7 Portfolio optimization using simulated annealing and quantum-inspired simulated annealing: A comparative study
- Chapter 8 Design of vehicular ad hoc network using IoT based on particle swarm optimization technique
- Chapter 9 Modeling and parametric optimization of grinding process using flower pollination algorithm
- Chapter 10 New quantum-inspired salp swarm algorithm: A comparative study on numerical computation
- Chapter 11 A fuzzy soft coronavirus alarm model
- Chapter 12 Conclusion and future research directions
- Index