Application of artificial neural networks to predict the heavy metal contamination in the Bartin River
Yazarlar (6)
Prof. Dr. Handan Ucun Özel Bartın Üniversitesi, Türkiye
Doç. Dr. Betül Tuba Gemici Bartın Üniversitesi, Türkiye
Dr. Öğr. Üyesi Ercan Gemici Bartın Üniversitesi, Türkiye
Prof. Dr. Halil Barış Özel Bartın Üniversitesi, Türkiye
Prof. Dr. Mehmet Çetin Kastamonu Üniversitesi, Türkiye
Prof. Dr. Hakan ŞEVİK Kastamonu Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Environmental Science and Pollution Research | ||
| Dergi ISSN | 0944-1344 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2020 |
| Kabul Tarihi | 15-07-2020 | Yayınlanma Tarihi | 24-07-2020 |
| Cilt / Sayı / Sayfa | 27 / 34 / 42495–42512 | DOI | 10.1007/s11356-020-10156-w |
| Makale Linki | http://link.springer.com/10.1007/s11356-020-10156-w | ||
| UAK Araştırma Alanları |
Silvikültür
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| Özet |
| In this study, copper (Cu), iron (Fe), zinc (Zn), manganese (Mn), nickel (Ni), and lead (Pb) analyses were performed, and the results were modelled by artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Samples were taken from 3 stations selected on the Bartin River for 1 year between December 2012 and December 2013. Radial basis neural network (RBANN), multilayer perceptron (MLP) neural networks models, and adaptive neuro-fuzzy inference system (ANFIS) were applied to the data in order to predict the heavy metal concentrations. As a result of the study, the RMSE and MAE values of all the heavy metal models were found to have very low error values during the test phase, and it was found that the models created using MLP had R2 values higher than 0.77 during the test phase; the test phase R2 values of the models using RBN method were found to be ranging between … |
| Anahtar Kelimeler |
| ANFIS model | ANN | Bartin River | Contamination | Heavy metal | River |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 130 |
| Scopus | 147 |
| Google Scholar | 194 |