Description
Multilevel Quantum Metaheuristics: Applications in Data Exploration explores the most recent advances in hybrid quantum-inspired algorithms. Combining principles of quantum mechanics with metaheuristic techniques for efficient data optimization, this book examines multilevel quantum systems characterized by qudits and higher-level quantum states as more robust alternatives to conventional bilevel quantum approaches. It introduces novel multilevel applications of quantum metaheuristics for addressing optimization problems in areas including function optimization, data analysis, scheduling, and signal processing. The book also showcases real-world examples, case studies, and contributions that emphasize the effectiveness of proposed multilevel techniques over existing bilevel methods. Researchers, professionals, and engineers working on intelligent computing, quantum computing, data processing, clustering, and analysis, and those interested in the synergies between quantum computing, metaheuristics, and multilevel quantum systems for enhanced data exploration and analysis will find this book to be of great value.- Provides insights into the future of quantum-inspired optimization by covering recent trends and mathematical techniques- Advances knowledge of evolving time-efficient hybrid quantum algorithms that leverage the processing capabilities of emerging qudit-based paradigms- Presents in-depth analysis of quantum mechanical principles with special reference to multilevel quantum states
Table of Contents
1. Multilevel Quantum Metaheuristics: Fundamentals and Applications2. Multilevel Quantum Metaheuristics and Their Role in Data-Intensive Applications3. Beyond Qubits: Exploring Molecular Spin Qudits for Advanced Quantum Computing4. Neural Architecture Search Using a Quantum Genetic Algorithm for Image Classification5. Revolutionizing Network Optimization: Enhancing Efficiency and Performance through Quantum Computing and Hybrid Quantum-Classical Approaches6. Automated Cluster Number Detection in Hyperspectral Images Using a Qutrit Flower Pollination Algorithm7. Multi objective portfolio optimization using multilevel quantum-inspired optimization algorithms: A comparative study8. A Comprehensive Performance Analysis of the Quantum-Inspired Genetic Algorithm for Image Segmentation9. Quantum-Inspired Metaheuristics for Drug Design and Discovery10. Application of Quantum Metaheuristics Techniques in Data Exploration for IoT Environment11. Task Allocation and Scheduling12. Image Processing and Signalling in Multilevel Quantum Metaheuristics13. AQIMLQC : A Framework for Advancing Air Quality Prediction using Quantum-Inspired Metaheuristics on Climate Change to achieve positive health14. Quantum Approaches to Task Allocation and Scheduling: Enhancing Efficiency and Optimisation in Distributed Systems15. Multilevel Quantum Metaheuristics: Concluding Remarks and Future Directions of Research
