Theo dơi
Ozgur Kisi
Ozgur Kisi
Department of Civil Engineering, University of Applied Sciences, Lübeck, Germany
Email được xác minh tại th-luebeck.de
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Applications of hybrid wavelet–artificial intelligence models in hydrology: a review
V Nourani, AH Baghanam, J Adamowski, O Kisi
Journal of Hydrology 514, 358-377, 2014
7182014
Streamflow forecasting using different artificial neural network algorithms
Ö Kişi
Journal of Hydrologic Engineering 12 (5), 532-539, 2007
4652007
Two hybrid artificial intelligence approaches for modeling rainfall–runoff process
V Nourani, Ö Kisi, M Komasi
Journal of Hydrology 402 (1-2), 41-59, 2011
4142011
Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones
O Kisi
Hydrological sciences journal 50 (4), 2005
4132005
River flow modeling using artificial neural networks
Ö Kişi
Journal of Hydrologic Engineering 9 (1), 60-63, 2004
3942004
A wavelet-support vector machine conjunction model for monthly streamflow forecasting
O Kisi, M Cimen
Journal of Hydrology 399 (1-2), 132-140, 2011
3672011
Wavelet and neuro-fuzzy conjunction model for precipitation forecasting
T Partal, Ö Kişi
Journal of Hydrology 342 (1-2), 199-212, 2007
3672007
Comparison of Mann–Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey
O Kisi, M Ay
Journal of Hydrology 513, 362-375, 2014
3562014
Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution
O Kisi, KS Parmar
Journal of Hydrology 534, 104-112, 2016
3382016
Multi-layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation/Prévision et estimation de la concentration …
Ö Kisi
Hydrological Sciences Journal 49 (6), 2004
3362004
SVM, ANFIS, regression and climate based models for reference evapotranspiration modeling using limited climatic data in a semi-arid highland environment
H Tabari, O Kisi, A Ezani, PH Talaee
Journal of Hydrology 444, 78-89, 2012
3332012
Daily water level forecasting using wavelet decomposition and artificial intelligence techniques
Y Seo, S Kim, O Kisi, VP Singh
Journal of Hydrology 520, 224-243, 2015
3062015
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
ZM Yaseen, O Jaafar, RC Deo, O Kisi, J Adamowski, J Quilty, A El-Shafie
Journal of Hydrology 542, 603-614, 2016
2962016
Modeling rainfall-runoff process using soft computing techniques
O Kisi, J Shiri, M Tombul
Computers & Geosciences 51, 108-117, 2013
2952013
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
RC Deo, O Kisi, VP Singh
Atmospheric Research 184, 149-175, 2017
2872017
A genetic programming approach to suspended sediment modelling
A Aytek, Ö Kişi
Journal of hydrology 351 (3-4), 288-298, 2008
2792008
Solar radiation prediction using different techniques: model evaluation and comparison
L Wang, O Kisi, M Zounemat-Kermani, GA Salazar, Z Zhu, W Gong
Renewable and Sustainable Energy Reviews 61, 384-397, 2016
2772016
Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data
HK Cigizoglu, Ö Kişi
Hydrology Research 36 (1), 49-64, 2005
2752005
Comparison of three back-propagation training algorithms for two case studies
Ö Kişi, E Uncuoğlu
CSIR, 2005
2672005
Methods to improve the neural network performance in suspended sediment estimation
HK Cigizoglu, Ö Kisi
Journal of hydrology 317 (3-4), 221-238, 2006
2582006
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