Computational Intelligence for Water and Environmental Sciences
Computational Intelligence for Water and Environmental Sciences
edited by Omid Bozorg-Haddad, Babak Zolghadr-Asli
- 1st edition 2022
- 1 recurso en línea (XXI, 540 páginas) 157 ilustraciones, 80 ilustraciones a color
- Studies in Computational Intelligence 1043 1860-9503 .
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.
9789811925191
10.1007/978-981-19-2519-1 doi
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.
9789811925191
10.1007/978-981-19-2519-1 doi