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Computational Intelligence for Water and Environmental Sciences / edited by Omid Bozorg-Haddad, Babak Zolghadr-Asli

Contributor(s): Bozorg-Haddad, Omid, editor literario | Zolghadr-Asli, Babak, editor literario
Series: (Studies in Computational Intelligence, 1860-9503; 1043).Publisher: Singapore : Springer International Publishing, 2022Edition: 1st edition 2022.Description: 1 recurso en línea (XXI, 540 páginas) : 157 ilustraciones, 80 ilustraciones a color.ISBN: 9789811925191.Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Optimization Algorithms -- Data mining -- Machine Learning -- Artificial Intelligence -- Deep Learning -- Expert Systems -- Probabilistic Models -- Bayesian models -- Fuzzy logic and Fuzzy Theory.
Summary: 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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Holdings
Item type Current library Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Acceso electrónico eBook.25122971
Total holds: 0

Optimization Algorithms -- Data mining -- Machine Learning -- Artificial Intelligence -- Deep Learning -- Expert Systems -- Probabilistic Models -- Bayesian models -- Fuzzy logic and Fuzzy Theory.

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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