Metaheuristics for Machine Learning

Kanak Kalita, PhD, is a professor in the Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, India. He has more than 190 articles in international and national journals and 5 edited books. Dr. Kalita’s research interests include machine learning, fuzzy decision-making, metamodeling, process optimization, finite element method, and composites. Narayanan Ganesh, PhD, is an associate professor at the Vellore Institute of Technology Chennai Campus. His extensive research encompasses a range of critical areas, including software engineering, agile software development, prediction and optimization techniques, deep learning, image processing, and data analytics. He has published over 30 articles and written 8 textbooks and has been recognized for his contributions to the field with two international patents from Australia. S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.

• Foreword xvPreface xvii1 Metaheuristic Algorithms and Their Applications in Different Fields: A Comprehensive Review 1Abrar Yaqoob, Navneet Kumar Verma and Rabia Musheer Aziz1.1 Introduction 21.2 Types of Metaheuristic Algorithms 31.3 Application of Metaheuristic Algorithms 201.4 Future Direction 251.5 Conclusion 262 A Comprehensive Review of Metaheuristics for Hyperparameter Optimization in Machine Learning 37Ramachandran Narayanan and Narayanan Ganesh2.1 Introduction 382.2 Fundamentals of Hyperparameter Optimization 392.3 Overview of Metaheuristic Optimization Techniques 422.4 Population-Based Metaheuristic Techniques 432.5 Single Solution-Based Metaheuristic Techniques 472.6 Hybrid Metaheuristic Techniques 492.7 Metaheuristics in Bayesian Optimization 502.8 Metaheuristics in Neural Architecture Search 532.9 Comparison of Metaheuristic Techniques for Hyperparameter Optimization 552.10 Applications of Metaheuristics in Machine Learning 612.11 Future Directions and Open Challenges 632.12 Conclusion 653 A Survey of Computer-Aided Diagnosis Systems for Breast Cancer Detection 73Charu Anant Rajput, Leninisha Shanmugam and Parkavi K.3.1 Introduction 733.2 Procedure for Research Survey 773.3 Imaging Modalities and Their Datasets 773.4 Research Survey 833.5 Conclusion 903.6 Acknowledgment 914 Enhancing Feature Selection Through Metaheuristic Hybrid Cuckoo Search and Harris Hawks Optimization for Cancer Classification 95Abrar Yaqoob, Navneet Kumar Verma, Rabia Musheer Aziz and Akash Saxena4.1 Introduction 964.2 Related Work 994.3 Proposed Methodology 1044.4 Experimental Setup 1154.5 Results and Discussion 1194.6 Conclusion 1305 Anomaly Identification in Surveillance Video Using Regressive Bidirectional LSTM with Hyperparameter Optimization 135Rajendran Shankar and Narayanan Ganesh5.1 Introduction 1365.2 Literature Survey 1375.3 Proposed Methodology 1385.4 Result and Discussion 1435.5 Conclusion 1466 Ensemble Machine Learning-Based Botnet Attack Detection for IoT Applications 149Suchithra M.6.1 Introduction 1506.2 Literature Survey 1516.3 Proposed System 1526.4 Results and Discussion 1566.5 Conclusion 1607 Machine Learning-Based Intrusion Detection System with Tuned Spider Monkey Optimization for Wireless Sensor Networks 163Ilavendhan Anandaraj and Kaviarasan Ramu7.1 Introduction 1647.2 Literature Review 1667.3 Proposed Methodology 1687.4 Result and Discussion 1737.5 Conclusion 1778 Security Enhancement in IoMT--Assisted Smart Healthcare System Using the Machine Learning Approach 179Jayalakshmi Sambandan, Bharanidharan Gurumurthy and Syed Jamalullah R.8.1 Introduction 1808.2 Literature Review 1828.3 Proposed Methodology 1848.4 Conclusion 1929 Building Sustainable Communication: A Game-Theoretic Approach in 5G and 6G Cellular Networks 195Puppala Ramya, Tulasidhar Mulakaluri, Chebrolu Yasmina, Pandi Bindu Madhavi and Vijay Guru Balaji K. S.9.1 Introduction 1969.2 Related Works 1969.3 Methodology 1979.4 Result 2079.5 Conclusion 21110 Autonomous Vehicle Optimization: Striking a Balance Between Cost-Effectiveness and Sustainability 215Vamsidhar Talasila, Sagi Venkata Lakshmi Narasimharaju, Neeli Veda Vyshnavi, Saketh Naga Sreenivas Kondaveeti, Garimella Surya Siva Teja and Kiran Kumar Kaveti10.1 Introduction 21610.2 Methods 21910.3 Results 22410.4 Conclusions 23111 Adapting Underground Parking for the Future: Sustainability and Shared Autonomous Vehicles 235Vamsidhar Talasila, Madala Pavan Pranav Sai, Gade Sri Raja Gopala Reddy, Vempati Pavan Kashyap, Gunda Karthik and K. V. Panduranga Rao11.1 Introduction 23611.2 Related Works 23711.3 Methodology 23811.4 Analysis 24511.5 Conclusion 25012 Big Data Analytics for a Sustainable Competitive Edge: An Impact Assessment 253Rajyalakshmi K., Padma A., Varalakshmi M., Suhasini A. and Chiranjeevi P.12.1 Introduction 25412.2 Related Works 25512.3 Hypothesis and Research Model 25512.4 Results 25912.5 Conclusion 26413 Sustainability and Technological Innovation in Organizations: The Mediating Role of Green Practices 267Rajyalakshmi K., Rajkumar G. V. S., Sulochana B., Rama Devi V. N. and Padma A.13.1 Introduction 26813.2 Related Work 26913.4 Discussion 27913.5 Conclusions 28114 Optimal Cell Planning in Two Tier Heterogeneous Network through Meta-Heuristic Algorithms 285Sanjoy Debnath, Amit Baran Dey and Wasim Arif14.1 Introduction 28514.2 System Model and Formulation of the Problem 28814.3 Result and Discussion 29514.4 Conclusion 29815 Soil Aggregate Stability Prediction Using a Hybrid Machine Learning Algorithm 301M. Balamurugan15.1 Introduction 30215.2 Related Works 30315.3 Proposed Methodology 30315.4 Result and Discussion 30915.5 Conclusion 313References 313Index 315