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Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm's background and the fields it has been used in.Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.
This book provides a comprehensive yet fresh perspective for the cutting-edge CI-oriented approaches in water resources planning and management. The book takes a deep dive into topics like meta-heuristic evolutionary optimization algorithms (e.g., GA, PSA, etc.), data mining techniques (e.g., SVM, ANN, etc.), probabilistic and Bayesian-oriented frameworks, fuzzy logic, AI, deep learning, and expert systems. These approaches provide a practical approach to understand and resolve complicated and intertwined real-world problems that often imposed serious challenges to traditional deterministic precise frameworks. The topic caters to postgraduate students and senior researchers who are interested in computational intelligence approach to issues stemming from water and environmental sciences.
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