Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Onur Genc"'
Autor:
Yasar Subutay Peker, Mehmet Fatih Can, Ismail Hakki Ozerhan, Gokhan Yagci, Nazif Zeybek, Kutan Kavakli, Sedat Gurkok, Alper Gozubuyuk, Onur Genc, Gokhan Erdem, Ahmet Ozet, Mustafa Gerek, Yusuf Peker
Publikováno v:
Case Reports in Surgery, Vol 2018 (2018)
The main method of fighting against colon cancer is targeted treatment. BRAF inhibitors, which are accepted as standard treatment for V600E mutant malign melanomas, are the newest approach for targeted treatment of V600E mutant colorectal cancers. In
Externí odkaz:
https://doaj.org/article/17753d1cf366468c9b94b7a4d65b2878
Publikováno v:
The Annals of Thoracic Surgery. 114:e257-e259
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d2dd9d32fc792b17481ab58906e71b5
https://doi.org/10.1016/j.athoracsur.2021.12.008
https://doi.org/10.1016/j.athoracsur.2021.12.008
Publikováno v:
Journal of Business Analytics. 3:67-78
This study aims to develop a decision support tool for identifying the point velocity profiles in rivers. The tool enables managers to make timely and accurate decisions, thereby eliminating a subs...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5006e3b4eb4ddbd50e2dce7608b09f3
https://doi.org/10.1080/2573234x.2020.1751569
https://doi.org/10.1080/2573234x.2020.1751569
Publikováno v:
Journal of Water and Climate Change. 11:390-401
Accurate estimation of velocity distribution in open channels or streams (especially in turbulent flow conditions) is very important and its measurement is very difficult because of spatio-temporal variation in velocity vectors. In the present study,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce9338eae1fed4929891c7920ecf83e2
https://doi.org/10.2166/wcc.2019.103
https://doi.org/10.2166/wcc.2019.103
Publikováno v:
Water Resources Management. 30:43-61
This article addresses the determination of velocity profile in small streams by employing powerful machine learning algorithms that include artificial neural networks (ANNs), support vector machine (SVMs), and k-nearest neighbor algorithms (k-NN). T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9d9c923535ccd2358d6b80392d0bae0
https://doi.org/10.1007/s11269-015-1123-7
https://doi.org/10.1007/s11269-015-1123-7
Publikováno v:
Journal of Hydroinformatics. 18:466-480
Developing a reliable data analytical method for predicting the velocity profile in small streams is important in that it substantially decreases the amount of money and effort spent on measurement procedures. In recent studies it has been shown that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b213d2a21e7835765bc0298acfdafd12
https://doi.org/10.2166/hydro.2015.110
https://doi.org/10.2166/hydro.2015.110
A comparative evaluation of shear stress modeling based on machine learning methods in small streams
Publikováno v:
Journal of Hydroinformatics. 17:805-816
Predicting shear stress distribution has proved to be a critical problem to solve. Hence, the basic objective of this paper is to develop a prediction of shear stress distribution by machine learning algorithms including artificial neural networks, c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3aa6b8a1a732e801228fa38e01258ccd
https://doi.org/10.2166/hydro.2015.142
https://doi.org/10.2166/hydro.2015.142
Publikováno v:
Geofizika
Volume 33
Issue 2
Volume 33
Issue 2
In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______951::9993788b84b76b3e0ac82cb00baa72e9
https://hrcak.srce.hr/file/254500
https://hrcak.srce.hr/file/254500
Publikováno v:
ICMLA
This study aims to reveal a reliable and efficient method for predicting the monthly evaporation. For this purpose, the accuracy of machine learning algorithms, MLA, that include k-nearest neighbor, k-NN, was used in modeling monthly evaporation. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ebf7e1bbf8b6290deeee41393bd8e33
https://doi.org/10.1109/icmla.2015.74
https://doi.org/10.1109/icmla.2015.74
Publikováno v:
Water and Environment Journal. 26:147-154
This paper examines the discharge and velocity distributions in natural open channel flows using the entropy theory. Flow measurements were carried out at four different cross-sections in central Turkey. The mean and maximum velocities at these stati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b2d97bf4efe1999b171eb554626597a
https://doi.org/10.1111/j.1747-6593.2011.00270.x
https://doi.org/10.1111/j.1747-6593.2011.00270.x