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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.
- Gives theoretical descriptions of each presented algorithm and
algorithm codes in a way that is easy to follow - Offers a robust
literature review for each algorithm - Useful for a range of
readers that may need to understand and apply optimization
- Gives theoretical descriptions of each presented algorithm and
algorithm codes in a way that is easy to follow - Offers a robust
literature review for each algorithm - Useful for a range of
readers that may need to understand and apply optimization
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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