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Author: Mohammad Zakwan
Publisher: Elsevier
ISBN: 0323985173
Category : Computers
Languages : en
Pages : 722
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Book Description
Water Resource Modeling and Computational Technologies, Seventh Edition provides the reader with a comprehensive overview of the applications that computational techniques have in various sectors of water resource engineering. The book explores applications of recent modeling and computational techniques in various sectors of water resource engineering, including hydroinformatics, irrigation engineering, climate change, hydrologic forecasting, floods, droughts, image processing, GIS, water quality, aquifer mapping, basin scale modeling, computational fluid dynamics, numerical modeling of surges and groundwater flow, river engineering, optimal reservoir operation, multipurpose projects, and water resource management. As such, this is a must read for hydrologists, civil engineers and water resource managers. Presents contributed chapters from global experts in the field of water resources from both a science and engineering perspective Includes case studies throughout, providing readers with an opportunity to understand how case specific challenges can help with computational techniques Provides basic concepts as well as a literature review on the application of computational techniques in various sectors of water resources
Author: Mohammad Zakwan
Publisher: Elsevier
ISBN: 0323985173
Category : Computers
Languages : en
Pages : 722
Get Book Here
Book Description
Water Resource Modeling and Computational Technologies, Seventh Edition provides the reader with a comprehensive overview of the applications that computational techniques have in various sectors of water resource engineering. The book explores applications of recent modeling and computational techniques in various sectors of water resource engineering, including hydroinformatics, irrigation engineering, climate change, hydrologic forecasting, floods, droughts, image processing, GIS, water quality, aquifer mapping, basin scale modeling, computational fluid dynamics, numerical modeling of surges and groundwater flow, river engineering, optimal reservoir operation, multipurpose projects, and water resource management. As such, this is a must read for hydrologists, civil engineers and water resource managers. Presents contributed chapters from global experts in the field of water resources from both a science and engineering perspective Includes case studies throughout, providing readers with an opportunity to understand how case specific challenges can help with computational techniques Provides basic concepts as well as a literature review on the application of computational techniques in various sectors of water resources
Author: Carlos A. Brebbia
Publisher:
ISBN: 9780945824480
Category : Hydrology
Languages : en
Pages : 588
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Book Description
Author: G. Tayfur
Publisher: WIT Press
ISBN: 1845646363
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.
Author: International Conference on Computational Methods in Water Resources (10, 1994, Heidelberg)
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Driss Ben Sari
Publisher: Computational Mechanics
ISBN: 9781853121593
Category : Hydrology
Languages : en
Pages : 322
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Book Description
Author: T. F. Russell
Publisher: Computational Mechanics
ISBN: 9781562520984
Category : Hydrology
Languages : en
Pages : 0
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Book Description
Author: T. F. Russell
Publisher: Computational Mechanics
ISBN: 9781853121692
Category : Science
Languages : en
Pages : 820
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Book Description
Author:
Publisher:
ISBN: 9780444416698
Category : Hydrology
Languages : en
Pages :
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Book Description
Author: G. Tayfur
Publisher:
ISBN: 9781845646370
Category : Computers
Languages : en
Pages : 289
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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.
Author: M. A. Celia
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
