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Computational intelligence for water and environmental sciences

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational intelligence for water and environmental sciencesedited by Omid Bozorg-Haddad, Babak Zolghadr-Asli.
other author:	Bozorg-Haddad, Omid.
Published:	Singapore :Springer Nature Singapore :2022.
Description:	xxi, 540 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computational intelligence.
Online resource:	https://doi.org/10.1007/978-981-19-2519-1
ISBN:	9789811925191$q(electronic bk.)

Computational intelligence for water and environmental sciences
Computational intelligence for water and environmental sciences[electronic resource] /edited by Omid Bozorg-Haddad, Babak Zolghadr-Asli. - Singapore :Springer Nature Singapore :2022. - xxi, 540 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 10431860-9503 ;. - Studies in computational intelligence ;v. 216..

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.

ISBN: 9789811925191$q(electronic bk.)

Standard No.: 10.1007/978-981-19-2519-1doiSubjects--Topical Terms:

210824
Computational intelligence.

LC Class. No.: Q342 / .C65 2022

Dewey Class. No.: 006.3

Computational intelligence for water and environmental sciences
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245 0 0 $a Computational intelligence for water and environmental sciences $h [electronic resource] / $c edited by Omid Bozorg-Haddad, Babak Zolghadr-Asli.
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300 $a xxi, 540 p. : $b ill. (some col.), digital ; $c 24 cm.
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505 0 $a Optimization Algorithms -- Data mining -- Machine Learning -- Artificial Intelligence -- Deep Learning -- Expert Systems -- Probabilistic Models -- Bayesian models -- Fuzzy logic and Fuzzy Theory.
520 $a 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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650 0 $a Environmental sciences $x Technological innovations. $3 928444
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950 $a Intelligent Technologies and Robotics (SpringerNature-42732)