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\par \quad  This edited volume, {\bf{Principles of Hybrid Intelligent Systems}}, is conceived in response to the growing need for intelligent solutions that transcend the limitations of single-model artificial intelligence approaches. As real-world problems become increasingly complex, dynamic, and data-rich, hybrid intelligent systems-integrating machine learning, deep learning, classical AI, signal processing, optimization, and domain expertise-have emerged as a powerful and practical paradigm. This book brings together contributions from researchers and academicians across diverse application domains to present both foundational principles and real-world implementations of hybrid intelligence. The chapters collectively demonstrate how synergistic model integration enhances robustness, interpretability, and decision-making capability, while also addressing societal, industrial, and technological challenges. It is our hope that this volume will serve as a valuable reference for researchers, educators, postgraduate students, and practitioners, and will inspire further innovation and research in the rapidly evolving field of hybrid intelligent systems. 
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