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Başlık: Application of trend analysis and artificial neural networks methods: The case of Sakarya River
Yazarlar: Çeribaşı, Gökhan
Doğan, Emrah
Akkaya, Uğur
Uludağ Üniversitesi/Karacabey Meslek Yüksekokulu/Bilgisayar Teknolojisi Bölümü.
0000-0003-1172-9465
Kocamaz, Uğur Erkin
55549566400
Anahtar kelimeler: Engineering
Trend analysis
Artificial neural networks
Sakarya river
Rainfall
Stream flow
Suspended load
Turkey
Neural networks
Rain
Rivers
ANN modeling
Annual average
Annual rainfall
Artificial intelligence techniques
Monthly rainfalls
Artificial intelligence
Suspended loads
Artificial neural network
Data processing
Yayın Tarihi: 5-Eyl-2016
Yayıncı: Sharif University Technology
Atıf: Çeribaşı, G. vd. (2017). ''Application of trend analysis and artificial neural networks methods: The case of Sakarya River''. Scientia Iranica, 24(3), 993-999.
Özet: Various artificial intelligence techniques are used in order to make prospective estimations with available data. The most common and applied method among these artificial intelligence techniques is Artificial Neural Networks (ANN). On the other hand, another method which is used in order to make prospective estimations with available data is Trend Analysis. When the relation of these two methods is analyzed, Artificial Neural Networks method can present the prospective estimation numerically, while there is no such a case in Trend Analysis. Trend Analysis method presents result of prospective estimation as a decrease or increase in data. Therefore, it is quite important to make a comparison between these methods which brings about prospective estimation with the available data, because these two methods are used in most of these studies. In this study, annual average stream flow and suspended load measured in Sakarya River along with average annual rainfall trend were analyzed with trend analysis method. Daily, weekly, and monthly average stream flows and suspended loads measured in Sakarya River and average daily, weekly, and monthly rainfall data of Sakarya were all analyzed by ANN Model. Results of trend analysis method and ANN model were compared.
URI: https://doi.org/10.24200/sci.2017.4082
http://scientiairanica.sharif.edu/article_4082.html
http://hdl.handle.net/11452/32141
ISSN: 1026-3098
Koleksiyonlarda Görünür:Scopus
Web of Science

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