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A Hydrodynamic Neural Network Model For The River Thames


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  • Product Description

River modelling has to overcome difficulties such as lack of complete measured data or incomplete data, complicated hydrodynamic equations and turbulence. Since neural networks can simulate directly from the given data, without any a priori equations, they can overcome many if not all of these difficulties. Beginning with an introduction to neural networks, the work then considers the application of such hydroinformatic techniques to river/estuarine modelling. Neural network models with and without bottom friction are developed using the backpropagation algorithm and appropriate optimum learning rates and momentum term parameters are calculated. Finally, these models are applied to the confluence of the Rivers Thames and Medway. Appendices: finite differences, Matlab code, support vector machines. This book should be of interest to any researcher or student involved in the application of artificial intelligence to river modelling.

Product Specifications
SKU :COC17267
AuthorLyn Rees
Number of Pages304
Publishing Year2012-09-10T00:00:00.000
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-26 00:00:00
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