چکیده مقاله
This study proposed a hybrid pre processing approach along with a conceptual model to enhance the accuracy of river discharge prediction In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm EEMD , Discrete Wavelet Transform DWT and Mutual Information MI were employed as a hybrid pre processing approach conjugated to Least Square Support Vector Machine LSSVM A conceptual strategy namely multi station model was developed to forecast the Souris River discharge more accurately The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling DWT and EEMD was coupled and feature selection was performed for decomposed sub series using MI to be employed in multi station model In the proposed feature selection method, some useless sub series were omitted to achieve better performance Results approved efficiency of the proposed DWT EEMD MI approach to improve accuracy of multi station modeling strategies
کلیدواژهها
نویسندگان
Alireza Faregh Gharamaleki
M Sc East Azerbaijan regional water company, Tabriz, East Azerbaijan, Iran
Farhad Alizadeh
Ph D candidate East Azerbaijan regional water company
Ali Akhoundzadeh
M Sc East Azerbaijan regional water company, Tabriz, East Azerbaijan, Iran
Khadije Tabatabaee
M Sc East Azerbaijan regional water company, Tabriz, East Azerbaijan, Iran
شیوه ارجاع
Faregh Gharamaleki, Alireza and Alizadeh, Farhad and Akhoundzadeh, Ali and Tabatabaee, Khadije,1397,Multi-station prediction of river stage-discharge using EEMD-WT-LSSVM,11th International River Engineering Conference,Ahvaz
ارائهشده در
مجموعه مقالات یازدهمین سمینار بین المللی مهندسی رودخانه9 بهمن 1397 · اهواز