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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151622
Doc. No : ET23414
Main Entry : Abdalla Moharned Taha Shigidi
Title Proper : SOLVING THE INVERSE PROBLEM IN GROUNDWATER FLOW BY ITERATIVE INVERSION OF A NEURAL NETWORK
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : A new methodology for solving the inverse problem in groundwater hydrology isdeveloped and applied to a synthetic case study. An innovative aspect of the methodologyis the use of a data driven approximation of the groundwater flow equation to calibrate anumerical model for a steady state groundwater system. An ArtificiaI Neural Network(ANN) was successfully trained to produce the resulting hydraulic map when a completetransmissivity fieid is prescribed. The trained network was then iteratively inverted tomatch the prior information on transmissivity as well as piezometric head measurements.The hydraulic head maps resulting from the transmissivity field produczd by the invertedANN. are in good agreement with the hydraulic head maps produced from the originalsynthetic transmissivity field. The study shows that there is no unique solution to theinverse problem. and that an ensemble of solutions.....-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46653.pdf
Title and statement of responsibility and : SOLVING THE INVERSE PROBLEM IN GROUNDWATER FLOW BY ITERATIVE INVERSION OF A NEURAL NETWORK [Thesis]
 
 
 
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