Nature-Inspired Intelligence for Complex Problems - Rilegato

Rilegato

ISBN 10: 1394409702 ISBN 13: 9781394409709

Casa editrice: Wiley-Scrivener, 2026

Riassunto

Discover how to turn nature’s best problem-solving strategies into powerful computational tools with this comprehensive guide to building resilient, adaptive, and next-generation algorithms for healthcare, finance, and engineering.

Nature-inspired intelligence is a rapidly evolving field that draws from biological and physical phenomena, such as evolution, swarm behavior, neural processing, and immune systems, to develop algorithms capable of handling complexity, uncertainty, and scalability. Unlike conventional computational approaches, these techniques adapt dynamically, mimic resilience, and exhibit problem-solving strategies observed in nature. As industries face increasingly complex and data-intensive challenges, nature-inspired intelligence provides robust, efficient, and innovative solutions, positioning it as a cornerstone of future technological and scientific progress.

This book presents a comprehensive exploration of how biological, physical, and ecological principles can be transformed into powerful computational tools for solving some of today’s most challenging problems. Drawing inspiration from natural processes, the book highlights a broad spectrum of algorithms that push beyond traditional approaches to optimization and decision-making. Blending theory with application, the book demonstrates how nature-inspired intelligence can address complexity across domains including healthcare, energy, finance, engineering, and emerging technologies.

Readers will find the volume:

• Offers an in-depth exploration of a wide range of nature-inspired computational techniques, including evolutionary algorithms, swarm intelligence, neural models, and physics-inspired methods;
• Bridges the gap between natural systems and computational problem-solving, appealing to a diverse audience of researchers and practitioners;
• Features case studies in robotics, healthcare, finance, engineering, and environmental sustainability, and highlights how these algorithms are used to tackle practical challenges across industries;
• Addresses the latest advancements in combining multiple nature-inspired techniques and explores cutting-edge topics like quantum computing and bio-hybrid systems. ensuring the content remains relevant to current research and innovation.

Audience

Computer scientists, engineers, applied mathematicians, data scientists, and researchers in optimization and complex systems, as well as professionals in healthcare, energy, finance, and technology seeking innovative problem-solving approaches.

Su questo libro

Informazioni sull'autore

Abhishek Kumar, PhD is an Assistant Director and Professor in the Computer Science and Engineering Department, Chandigarh University, Mohali, Punjab, India. He has more than 230 publications to his credit, including books, chapters in books, and journal articles. His research interests span artificial intelligence, renewable energy systems, image processing, and data mining.

Priya Batta, PhD is an Associate Professor in the Computer Science and Engineering Department, Amity University, Mohali, Punjab, India. She received her Doctorate in Computer Science and Engineering from Chandigarh University. Her research specializes in artificial intelligence, blockchain, and IoT.

J.P. Ananth, PhD is a Professor and Director of the Internal Quality Assurance Cell, Dayananda Sagar University, Bangalore, India, with more than 23 years of experience. He has published more than 60 articles in international journals and conferences. His research interests include computer vision, pattern recognition, artificial intelligence, and data analytics.

S. Oswalt Manoj, PhD is an Associate Professor in the Department of Computer Science and Engineering, Alliance University, Bengaluru, Karnataka, India. He holds a Doctorate in Information Science and Engineering from Anna University in Chennai. His research areas include big data analytics, artificial intelligence, computer vision, machine learning, deep learning, and cloud computing.

T. Ananth Kumar, PhD is an Associate Professor and Research Head in Computer Science and Engineering, IFET College of Engineering, Villupuram, Tamil Nadu, India. He has more than 250 publications to his credit, including books, book chapters, and articles in international journals and conferences. His fields of interest include networks on chips, computer architecture, and ASIC design.

Dalla quarta di copertina

Discover how to turn nature's best problem-solving strategies into powerful computational tools with this comprehensive guide to building resilient, adaptive, and next-generation algorithms for healthcare, finance, and engineering.

Nature-inspired intelligence is a rapidly evolving field that draws from biological and physical phenomena, such as evolution, swarm behavior, neural processing, and immune systems, to develop algorithms capable of handling complexity, uncertainty, and scalability. Unlike conventional computational approaches, these techniques adapt dynamically, mimic resilience, and exhibit problem-solving strategies observed in nature. As industries face increasingly complex and data-intensive challenges, nature-inspired intelligence provides robust, efficient, and innovative solutions, positioning it as a cornerstone of future technological and scientific progress.

This book presents a comprehensive exploration of how biological, physical, and ecological principles can be transformed into powerful computational tools for solving some of today's most challenging problems. Drawing inspiration from natural processes, the book highlights a broad spectrum of algorithms that push beyond traditional approaches to optimization and decision-making. Blending theory with application, the book demonstrates how nature-inspired intelligence can address complexity across domains including healthcare, energy, finance, engineering, and emerging technologies.

Readers will find the volume:

• Offers an in-depth exploration of a wide range of nature-inspired computational techniques, including evolutionary algorithms, swarm intelligence, neural models, and physics-inspired methods;
• Bridges the gap between natural systems and computational problem-solving, appealing to a diverse audience of researchers and practitioners;
• Features case studies in robotics, healthcare, finance, engineering, and environmental sustainability, and highlights how these algorithms are used to tackle practical challenges across industries;
• Addresses the latest advancements in combining multiple nature-inspired techniques and explores cutting-edge topics like quantum computing and bio-hybrid systems. ensuring the content remains relevant to current research and innovation.

Audience

Computer scientists, engineers, applied mathematicians, data scientists, and researchers in optimization and complex systems, as well as professionals in healthcare, energy, finance, and technology seeking innovative problem-solving approaches.

Dettagli dell'edizione

• Editore: Wiley-Scrivener
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 1394409702
• ISBN 13: 9781394409709
• Rilegatura: Tapa dura
• Numero di pagine: 592
• Redattore: Kumar Abhishek, Batta Priya, Ananth J. P., Manoj S. Oswalt, Kumar T. Ananth
• Contatto del produttore: Easy Access System Europe Oü, 16879218; gpsr.requests@easproject.com; ; Mustamäe tee 50, 10621, Tallinn, Estonia; Tallinn; 10621; Estonia