A genetic programming approach to suspended sediment modelling A Aytek, Ö Kişi Journal of hydrology 351 (3-4), 288-298, 2008 | 283 | 2008 |
Sea water level forecasting using genetic programming and comparing the performance with artificial neural networks MA Ghorbani, R Khatibi, A Aytek, O Makarynskyy, J Shiri Computers & geosciences 36 (5), 620-627, 2010 | 187 | 2010 |
Stochastic generation of hourly mean wind speed data H Aksoy, ZF Toprak, A Aytek, NE Ünal Renewable energy 29 (14), 2111-2131, 2004 | 187 | 2004 |
New approach for stage–discharge relationship: gene-expression programming A Guven, A Aytek Journal of Hydrologic Engineering 14 (8), 812-820, 2009 | 184 | 2009 |
An application of artificial intelligence for rainfall-runoff modeling A Aytek, M Asce, M Alp Journal of Earth System Science 117, 145-155, 2008 | 176 | 2008 |
Genetic programming‐based empirical model for daily reference evapotranspiration estimation A Guven, A Aytek, MI Yuce, H Aksoy Clean–Soil, Air, Water 36 (10‐11), 905-912, 2008 | 113 | 2008 |
Co-active neurofuzzy inference system for evapotranspiration modeling A Aytek Soft Computing 13, 691-700, 2009 | 108 | 2009 |
Discussion of “Generalized regression neural networks for evapotranspiration modelling” MIYNEU Hafzullah Aksoy , Aytac Guven , Ali Aytek Hydrological Sciences Journal 52 (4), 825-831, 2009 | 60* | 2009 |
An explicit neural network formulation for evapotranspiration A Aytek, A Guven, MI Yuce, H Aksoy Hydrological sciences journal 53 (4), 893-904, 2008 | 49 | 2008 |
Rheological and strength performances of cold-bonded geopolymer made from limestone dust and bottom ash for grouting and deep mixing H Güllü, MMD Al Nuaimi, A Aytek Bulletin of Engineering Geology and the Environment 80, 1103-1123, 2021 | 44 | 2021 |
A genetic programming technique for lake level modeling A Aytek, O Kisi, A Guven Hydrology Research 45 (4-5), 529-539, 2014 | 18 | 2014 |
Explicit neural network in suspended sediment load estimation Ö Kisi, A Aytek Neural Network World 23 (6), 587, 2013 | 15 | 2013 |
A practical approach to formulate stage–discharge relationship in natural rivers A Guven, A Aytek, HM Azamathulla Neural Computing and Applications 23, 873-880, 2013 | 14 | 2013 |
Comment on ‘Kisi O. 2007. Evapotranspiration modelling from climatic data using a neural computing technique. Hydrological Processes 21: 1925–1934’ H Aksoy, A Guven, A Aytek, MI Yuce, NE Unal Hydrological Processes: An International Journal 22 (14), 2715-2717, 2008 | 12 | 2008 |
SPI ve SPEI ile Samsun ili kuraklık analizi Mİ Yüce, H Aksoy, A Aytek, E Musa, U Fetihhan, Y İslam, A Şimşek, ... Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 25 (3 …, 2022 | 7 | 2022 |
REPLY to Discussion of “An explicit neural network formulation for evapotranspiration” A Aytek, A Guven, MI Yuce, H Aksoy Taylor & Francis Group 54 (2), 389-393, 2009 | 4 | 2009 |
TÜRKİYE’NİN ULUSLARARASI SANAL SU TRANSFERİNİN İNCELENMESİ: BUĞDAY İÇİN BİR VAKA ANALİZİ A MURATOĞLU, Mİ YÜCE, A AYTEK | 1 | 2019 |
DOĞU AKDENİZ BÖLGESİ YAĞIŞ ŞİDDET-SÜRE-TEKERRÜR ANALİZİ İH Deger, Mİ Yüce, A Aytek Education 2021, 2020 | | 2020 |
Akarsu deltaları oluşumunun matematik modellenmesi A Aytek, N AĞIRALİOĞLU İTÜDERGİSİ/d 5 (5), 2011 | | 2011 |
11. ULUSAL HİDROLOJİ KONGRESİ Mİ YÜCE, A AYTEK, NK DSİ, G ÖZTÜRKMEN, M EŞİT, E ALKAN, ... | | |