4019

3795

كارشناسي ارشد

مهندسي آب

اصفهان: دانشگاه صنعتي اصفهان، دانشكده عمران

1386

هشت، 84، [II]ص.: مصور، جدول، نمودار

ص. ع. به فارسي و انگليسي

كيوان اصغري

مازيار پالهنگ

30/04/87

حميدرضا صفور، سعيد اسلاميان

1396/03/07

كتابنامه

عمران

مهندسي عمران

ID3795

به فارسي و انگليسي: قابل رؤيت در نسخه ديجيتال

Abstract Water scarcity climate changes and hydrological uncertainties emphasize the necessity of a comprehensive and meaningful management of water resources which will be achieved by reliable models Harnessing and appropriate using of surface water developing the groundwater resources alleviating the inverse impacts of flood or drought and healthy drinking water supply require models with accurate prediction Data driven modeling is new and rapidly expanded in scientific and engineering research areas This method in some situations would be a proper substitution for other modeling approaches such experimental and physical ones In this research the principles of a novel and advanced data driven technique called Support Vector Machines SVMs which is relied on statistical learning theory are discussed By applying this learning method generalization characteristic of the machine boosts and thus the model precision in comparison with other data driven techniques improves The aim of study is to present the underlying concepts of SVMs in order to learn complex physical processes and non linear behaviors of hydrological systems In this thesis the performance of learning machine is investigated within three various applications of water resources modeling consisting of 1 prediction of short term runoff 2 estimating the water level of a specific observation well and 3 spatial temporal forecasting of rainfall For implementing SVMs in the foregoing hydrological systems diverse combination of data is employed Analyzing and comparing the SVM results with the ones obtained through the artificial neural networks reveals the high prediction capability of SVM in the preceding applications The successful performance of SVMs throughout this research signifies the possibility of exploiting it in other water resources applications pdfMachine A pdf writer that produces quality PDF files with ease Produce quality PDF files in seconds and preserve the integrity of your original documents Compatible across nearly all Windows platforms simply open the document you want to convert click print select the Broadgun pdfMachine printer and that s it Get yours now

كيوان اصغري

مازيار پالهنگ

حميدرضا صفور، سعيد اسلاميان