Growth parameters with traditional and artificial neural networks methods of big-scale sand smelt (Atherina boyeri Risso, 1810)

Yıl 2023, Cilt: 40 Sayı: 2, 96 - 102, 15.06.2023

Semra Benzer Recep Benzer

https://doi.org/10.12714/egejfas.40.2.02

Öz

In this study, the growth parameters of big-scale sand smelt (Atherina boyeri Risso, 1810) in Iznik Lake has been determined with traditional (length weight relationships (LWRs), von Bertalanffy (VB), condition factor (CF)) and modern approaches (Artificial Neural Networks - ANNs). A total of 635 specimens (44.84% female and 55.16% male) were collected from the local fisherman during the hunting season between April 2018 to April 2019. Mean fork length (FL) (mm, min-max), mean W (g, min-max) and mean CF (value, min-max) were estimated as 67.31 mm (40.10 - 97.77 mm), 2.57 g (0.53 - 7.50 g), and 0.790 (0.170-1.520) for all individuals. The length weight relationships were determined W=0.00001437 L^2.8602 for female, W=0.00001570 L^2.8266 for male and W=0.00001328 L^2.8717 for all individuals. The von Bertalanffy equations were determined L_t=136.218 [1-e^(-0.240(t+0.51)) ] for female, L_t=155.042 [1-e^(-0.185(t+0.73)) ] for male, and L_t=146.916 [1-e^(-0.205(t+0.64)) ] for all individuals. The values in training (MSE (Mean Squared Error) 4.52559e-5, R (correlation coefficients) 9.09347e-1), verification (MSE 4.86111e-5, R2 9.00931e-1) and test data (MSE 3.391999e-5, R 9.43465e-1) were found in calculations made with ANNs. It was determined that ANNs could be an alternative for evaluating growth estimation.

Anahtar Kelimeler

Artificial Neural Networks, big-scale sand smelt, growth parameters, length weight relationships, von Bertalanffy

Destekleyen Kurum

Gazi University Project Resources Center Fund

Proje Numarası

BAP Project Number: 04/2018-05

Gümüş balığının (Atherina boyeri Risso, 1810) geleneksel ve yapay sinir ağları yöntemleriyle büyüme parametreleri

Öz

Bu çalışmada İznik Gölü'nde yakalanan gümüş balığının (Atherina boyeri Risso, 1810) büyüme parametreleri geleneksel (boy ağırlık ilişkileri (LWR), von Bertalanffy (VB) ve kondisyon faktörü (CF)) ve modern yaklaşımlarla (yapay sinir ağları) incelenmiştir. Av sezonunda bölge balıkçılarından Nisan 2018-Nisan 2019 tarihleri arasında toplam 635 adet (%44,84 dişi ve %55,16 erkek) birey toplanmıştır. Tüm populasyon için ortalama çatal boy (FL) 67,31 mm (40,10 - 97,77 mm), ortalama ağırlık (W) 2,57 g (0,53 - 7,50g) ve ortalama CF 0,790 (0,170-1,520) olarak bulunmuştur. LWR dişi popülasyon için W=0,00001437 L2,8602, erkek popülasyon için W=0,00001570 L2,8266 ve tüm popülasyon için W=0,00001328 L2,8717 olarak bulunmuştur. Von Bertalanffy dişi, erkek ve tüm popülasyonda sırasıyla L_t=136,218 [1-e^(-0,240(t+0,51)) ], L_t=155,042 [1-e^(-0,185(t+0,73)) ] ve L_t=146,916 [1-e^(-0,205(t+0,64)) ] olarak tespit edilmiştir. Yapay sinir ağları (ANN) ile yapılan hesaplamalarda eğitim, doğrulama ve test verilerindeki MSE (Ortalama Kare Hata) ve R (korelasyon katsayısı) değerleri sırasıyla 4.52559e-5 9.09347e-1, 4.86111e-5 9.00931e-1 ve 3.391999e-5 9.43465e-1 olarak bulunmuştur. YSA’ların büyüme tahmininin değerlendirilmesinde bir alternatif olabileceği belirlenmiştir.

Anahtar Kelimeler

Yapay sinir ağları, Gümüş Balığı, büyüme parametreleri, boy ağırlık ilişkileri, von Bertalanffy

Proje Numarası

BAP Project Number: 04/2018-05

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