Growth parameters with traditional and artificial neural networks methods of big-scale sand smelt (Atherina boyeri Risso, 1810)
Abstract
Keywords
Destekleyen Kurum
Proje Numarası
Kaynakça
- Bagenal, T.B., & Tesch, F.W. (1978). Age and growth. In T. Bagenal (Ed.), Methods for Assessment of Fish Production in Freshwaters (pp 101-136). Oxford: Blackwell Science Publications.
- Bartulovic, V., Glamuzina, B., Conides, A., Gavriloviç, A., & Dulçiç, J. (2006). Maturation, reproduction, and recruitment of the sand smelt, Atherina boyeri Risso, 1810 (Pisces: Atherinidae) in the estuary of Mala Neretva River (Southeastern Adriatic, Croatia). Acta Adriatica, 47(1), 5-11.
- Benzer, S. (2016). Growth Characteristics of Atherina boyeri Risso, 1880 in Mogan Lake. International Conference on Biological Sciences, Konya, Türkiye.
- Benzer, S. (2020). Artificial Neural Networks Approach to Growth Properties Atherina boyeri Risso 1810 in Yamula Dam Lake Turkey. Fresenius Environmental Bulletin, 29(2), 1145-1152.
- Benzer, S., & Benzer, R. (2016). Evaluation of growth in pike (Esox lucius L., 1758) using traditional methods and artificial neural networks. Applied Ecology and Environmental Research, 14(2), 543-554. https://doi.org/10.15666/aeer/1402_543554
- Benzer, S., & Benzer, R. (2017). Comparative growth models of big scale sand smelt Atherina boyeri Risso 1810 sampled from Hirfanlı Dam Lake Kırsehir Ankara Turkey. Computational Ecology and Software, 7(2), 82-90. https://doi.org/10.0000/issn-2220-721x-compuecol-2017-v7-0007
- Benzer, S., & Benzer, R. (2019). Alternative growth models in fisheries: Artificial Neural Networks. Journal of Fisheries, 7(3), 719-725.
- Benzer, S., & Benzer, R. (2020a). Growth Properties of Pseudorasbora parva in Süreyyabey Reservoir: Traditional and Artificial Intelligent Methods. Thalassas, 36(1), 149-156. https://doi.org/10.1007/s41208-020-00192-1
Ayrıntılar
Birincil Dil
İngilizce
Konular
Limnoloji , Balık Biyolojisi
Bölüm
Araştırma Makalesi
Erken Görünüm Tarihi
10 Haziran 2023
Yayımlanma Tarihi
15 Haziran 2023
Gönderilme Tarihi
2 Aralık 2022
Kabul Tarihi
30 Mart 2023
Yayımlandığı Sayı
Yıl 2023 Cilt: 40 Sayı: 2
Cited By
Comparison between traditional models and artificial neural networks as estimators of the growth of the Tigris scraper Capoeta umbla (Teleostei: Cyprinidae) in the Munzur River, Turkey
Revista Científica de la Facultad de Ciencias Veterinarias
https://doi.org/10.52973/rcfcv-e35513