دانلود کتاب رویکردهای الهام گرفته از کوانتوم برای پردازش هوشمند داده‌ها

The rise of advanced data-driven technologies has transformed the way we live, work, and interact with the world. With the exponential growth of data, conventional computing techniques often fall short in effectively handling challenges such as uncertainty, scalability, and complexity. Quantum inspired approaches offer a promising paradigm by leveraging principles from quantum mechanics to develop innovative models and algorithms that enhance intelligent data processing. This edited volume, Quantum-Inspired Approaches for Intelligent Data Processing, aims to bridge the gap between classical computing and the emerging quantum paradigm. It brings together contributions from leading researchers and practitioners worldwide, covering a wide spectrum of topics—from foundations of soft computing and quantum principles to applications in healthcare, finance, smart cities, cybersecurity, and beyond. The chapters provide theoretical insights, practical methodologies, and case studies that highlight how quantum-inspired techniques can address pressing computational challenges. By integrating fuzzy logic, evolutionary algorithms, neural networks, and hybrid systems with quantum-inspired models, the book showcases the potential of these methods in solving real world problems efficiently. We believe this book will serve as a valuable resource for researchers, academicians, and industry professionals seeking to explore cutting-edge advancements in intelligent data processing. It also offers an excellent reference for graduate students aiming to deepen their understanding of the interplay between quantum mechanics and soft computing. We express our sincere gratitude to all contributing authors for their dedication and scholarly work, and to the reviewers for their insightful feedback. We also thank Scrivener Publishing for their support and guidance throughout the publication process.