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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150724
Doc. No : ET22516
Main Entry : Abedalrazq F. Khalil
Title Proper : COMPUTATIONAL LEARNING AND DATA-DRIVEN MODELING FOR WATER RESOURCES MANAGEMENT AND HYDROLOGY
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Water scarcity, changing climate, and hydrologic uncertainty present seriouschallenges for water resources management and hydrologic modeling. Development ofsurface and groundwater resources, success in harnessing the power of flowing water,mitigation of the effects of floods and droughts, and provision for clean water requiremodels with high predictive capability. Computational learning theory and data-drivenmodeling techniques are new and rapidly expanding areas of research that examineformal models of induction with the goal of developing efficient learning algorithms.....-...,..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 : TL45738.pdf
Title and statement of responsibility and : COMPUTATIONAL LEARNING AND DATA-DRIVEN MODELING FOR WATER RESOURCES MANAGEMENT AND HYDROLOGY [Thesis]
 
 
 
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