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.

• Preface xxvPart I: Foundations and Introduction to Nature-Inspired Intelligence 11 Introduction to Nature-Inspired Intelligence 3Simarpreet Kaur and Vikas Wasson1.1 Overview of Nature-Inspired Computing 41.2 The Need for Bio-Inspired Solutions 91.3 Key Characteristics of Nature-Inspired Algorithms 181.4 Conclusion and Future Scope 202 Exploring Swarm Intelligence: A Comparative Analysis of Nature-Inspired Optimization Techniques 27Inderdeep Kaur and Aleem Ali2.1 Introduction to Swarm Intelligence 282.2 Fundamentals of Swarm Intelligence 302.3 Ant Colony Optimization (ACO) 342.4 Particle Swarm Optimization (PSO) 392.5 Grey Wolf Optimizer (GWO) 442.6 Comparative Analysis of Swarm Intelligence Algorithms 492.7 Applications of Swarm Intelligence Algorithms in Real-World Problems 532.8 Challenges and Future Research Directions 582.9 Conclusion 593 Swarm Dynamics in Optimization: A Deep Dive into PSO 63Benjamin Franklin S., Justin Jayaraj K., Monisha A., Balasubramaniam V., Sasi Kala and N.S. Kavitha3.1 Particle Swarm Optimization (PSO) 643.2 Engineering Designs in PSO 693.3 Variants of PSO 753.4 Swarm Intelligence in PSO 843.5 PSO in Healthcare and Logistic 863.6 Enhancements in PSO for Improved Performance 894 Genetic Algorithms: Fundamentals and Applications 97Satya Reddy Satti, Chanchal Alam, Ajay Sharma and Shamneesh Sharma4.1 Fundamentals of Genetic Algorithms 994.2 Mathematical Foundations of Genetic Algorithms 1024.3 Schema Theorem and Building Block Hypothesis 1024.4 Multi-Objective Optimization 1034.5 Applications of Genetic Algorithms 1064.6 Challenges and Mitigations 1104.7 Practical Implementation for Genetic Algorithms 1124.8 Future Directions in Genetic Algorithm Research 1145 Challenges and Future Directions in Nature-Inspired Intelligence 121Thayanithi C.A., Elipe Arjun and Priyanka Singh5.1 Introduction 1225.2 Contemporary Challenges 1245.3 Emerging Technologies and Trends 1305.4 Future Research Directions 1375.5 Implementation Strategies 1425.6 Impact Analysis 1485.7 Future Recommendations 1525.8 Conclusion 155Part II: Methods and Hybrid Models 1616 Hybrid Swarm Intelligence for Enhancing Optimization through Multi Swarm and Quantum Inspired Models in Decision Making and Robotics 163Barakkath Nisha U., Yasir Abdullah R., Sindhu V., Raihana A. and Anitha G.6.1 Introduction 1646.2 Background and Related Work 1676.3 Framework of Hybrid Swarm Intelligence 1716.4 Applications of Hybrid Swarm Intelligence 1756.5 Experimental Results and Performance Analysis 1796.6 Conclusion 1877 Swarm Intelligence and Differential Evolution in Robotics and Decision-Making 191Devendra Babu Pesarlanka, Abhinav Kumar, Ajay Sharma, Arun Malik and Shamneesh Sharma7.1 Introduction 1927.2 Fundamentals of Swarm Intelligence 1947.3 Key Swarm Intelligence Algorithms 1967.4 Particle Swarm Optimization (PSO) 2007.5 Applications of Swarm Intelligence in Robotics 2047.6 Swarm Intelligence in Decision-Making 207xiv Contents7.7 Challenges and Future Directions 2107.8 Conclusion 2138 Hybrid Nature-Inspired Systems: A Computational Intelligence Perspective 219Anitha Subbarayan8.1 Evolutionary Computation for Global Search Optimization 2208.2 Swarm Intelligence in Local Search and Refinement 2248.3 Neuro-Evolutionary Models for Adaptive Learning 2308.4 Hybridization Strategies for Balancing Exploration and Exploitation 2378.5 Co-Evolutionary and Memetic Algorithms 2388.6 Applications of Hybrid Nature-Inspired Systems 2398.7 Performance Metrics and Computational Efficiency of Hybrid Nature-Inspired Systems 2439 Optimizing Engineering Systems: Differential Evolution Algorithm and Hybrid Approaches for PID Controller 249G. Saravanan, C. Pazhanimuthu, P.N. Senthil Prakash and N.R. Wilfred Blessing9.1 Introduction 2509.2 Related Works 2529.3 Algorithms 2549.4 System Model 2619.5 Simulation Results and Discussion 27110 Novel Aspects of Ant Colony Optimization and Particle Swarm Optimization 279Rohan Gupta and Gurpreet Singh10.1 MANET Routing Strategies 28010.2 Routing Protocols 28110.3 Ant Based Routing Protocols 28610.4 PSO Routing Protocols 28710.5 Hybrid Routing Protocols 28810.6 Results and Discussion 28910.7 Conclusion 29211 Physics-Inspired Algorithms: Applications in Energy and Environmental Systems 297Naman Srivastava, Samyak Varia, Scaria Alex, Aswathy K. Cherian, Ashwini S. and Arshey M.11.1 Introduction 29811.2 Foundations of Physics-Inspired Algorithms (PIAs) 30111.3 Application of Physics-Inspired Algorithms (PIAs) in Energy Systems [1492 and 0%] 30811.4 Application of PIAs in Environmental Systems 31611.5 Case Studies and Real-Life Implementations 32211.6 Challenges and Way Forward 32511.7 Conclusion 329Part III: Applications Across Domains 33312 Optimization-Driven Deep CNN with PFCM Clustering for Enhanced MRI-Based Brain Tumor Detection 335P. Sathish, Sashikanth Reddy Avula and Channabasava12.1 Introduction 33612.2 Related Work 33712.3 Proposed Exponential Cuckoo-Based DCNN for Automatic Brain Tumor Classification 33912.4 Discussion of Results 34412.5 Summary 35313 Explainable AI and Ensemble Learning for Genetic Disorder Diagnosis Advancing Accuracy and Interpretabilityin Healthcare Predictions 357Ishdeep and Neetu Rani13.1 Introduction 35813.2 Literature Review 35913.3 Materials and Methods 36413.4 Results and Discussion 37513.5 Conclusion 38013.6 Future Scope 38114 Optimizing Complex Weights of Linear Antenna Array for Combating Real World Wireless Traffic Congestion 385Surekha Rani and Himanshu Sharma14.1 Introduction 38514.2 Problem Formulation 386xx Contents14.3 Simulation and Results 39214.4 Conclusion and Future Scope 40215 Nature-Inspired Intelligence for Enhanced Disease Detection in Medical Image Analysis 405R. Karthick Manoj, Aasha Nandhini S. and D. Lakshmi15.1 Introduction 40615.2 Related Work 40715.3 Proposed Methodology 40915.4 Result and Discussion 41715.5 Conclusion and Future Work 42516 Nature-Inspired Hybrid Model for Dysgraphia Diagnosis in Educational Settings 429A. Devi, B. Elizebeth Caroline, J. Vidhya, D. Sathish Kumar, T.D. Subha and L. Manimegalai16.1 Introduction 43016.2 Related Works 43416.3 Proposed Hybrid Model 44016.4 Feature Selection Using ACO 44916.5 Results and Discussions 45116.6 Conclusion 45717 Particle Swarm Optimization for Effective Feature Selection in Smart Logistics 461Asha K. and Nakul Ramesh Varma17.1 Introduction 46117.2 Particle Swarm Optimization 46217.3 Literature Survey 46917.4 Computational Analysis on Realtime-Case 47117.5 Legal and Ethical Considerations 47317.6 Methodology 47417.7 Implementation and Results 47617.8 Conclusion 47718 The Integration of IoT and Blockchain for Enhanced Security and Real-Time Updates 483Priya Batta and Abhishek Kumar18.1 Introduction 48318.2 Related Works 48818.3 Proposed Methodology 49118.4 Results and Discussions 49318.5 Conclusion and Future Scope 49419 Advancing Rehabilitation with Virtual Reality 497Charu Chhabra, Fowquiya, Sohrab A. Khan and Ifra Aman19.1 Introduction to Virtual Reality 49719.2 Methodology 49819.3 Literature 49819.4 Discussion 50819.5 Result 50919.6 Conclusion 509Part IV: Case Studies and Specific Implementations 51520 AI for Preserving Indian Knowledge Systems and Philosophy 517Aditya Atal, Shaurya Sharma and G.Y. Rajaa Vikhram20.1 Introduction 51820.2 AI in Preserving Ancient Hindu Texts and Literature 51820.3 AI-Driven Religious Chatbots and Q&A Systems 52020.4 AI and Digital Preservation of Oral Traditions and Folklore 52120.5 AI in Ayurveda and Traditional Healing 52220.6 AI in Yoga and Meditation Guidance 52320.7 AI-Powered Knowledge Systems for Hindu Ethics and Philosophy 52420.8 Role of AI in Hindu Astrology and Vedic Mathematics 52420.9 Ethical and Theological Considerations in AI-Based Hindu Studies 52520.10 Role of Blockchain and Quantum Computing in Hindu Knowledge Systems 52520.11 Future Scope and Challenges 53320.12 Conclusion and Research Directions 53820.13 Research Gaps and Areas for Further Exploration 54021 Nature-Inspired Algorithms and Their Applications: A Healthcare Case Study with the Bee Algorithm 543Puneet Kumar and Deepika Kumar21.1 Introduction 54421.2 Classification of Nature-Inspired Algorithms 54821.3 Bees Algorithm: Foundation 55121.4 Case Study: Bees Algorithm in Healthcare 556References 559Index 561