Machine Learning Applications for Fisheries—At Scales from Genomics to Ecosystems

B Kühn, A Cayetano, JI Fincham… - Reviews in Fisheries …, 2024 - Taylor & Francis
Fisheries science aims to understand and manage marine natural resources. It relies on
resource-intensive sampling and data analysis. Within this context, the emergence of …

Investigation of some machine learning algorithms in fish age classification

S Benzer, FH Garabaghi, R Benzer, HD Mehr - Fisheries Research, 2022 - Elsevier
Marine and freshwater scientists use fish scales, vertebrae, otoliths and length-weights
values to estimate fish age because reliable fish age estimation plays a very important role …

Effect of polynomial, radial basis, and Pearson VII function kernels in support vector machine algorithm for classification of crayfish

FH Garabaghi, R Benzer, S Benzer, AÇ Günal - Ecological Informatics, 2022 - Elsevier
Freshwater crayfish are one of the most important aquatic organisms that play a pivotal role
in the aquatic food chain as well as serving as bioindicators for the aquatic ecosystem health …

[PDF][PDF] Comparative growth models of big-scale sand smelt (Atherina boyeri Risso, 1810) sampled from Hirfanll Dam Lake, Klrsehir, Ankara, Turkey

S Benzer - Computational Ecology and Software, 2017 - iaees.org
In this current publication the growth characteristics of big-scale sand smelt data were
compared for population dynamics within artificial neural networks and length-weight …

[PDF][PDF] Artificial Neural Networks as new alternative method to estimating some population parameters of Tigris loach (Oxynoemacheilus tigris (Heckel, 1843)) in the …

Eİ ÖZCAN, O Serdar - 2018 - researchgate.net
In this study, a new method (Artificial Neural Networks) to estimating some population
parameters of Tigris loach (% &"!(Heckel, 1843)) collected between 2014 and 2015 in 14 …

Artificial Neural Networks approach in morphometric analysis of crayfish (Astacus leptodactylus) in Hirfanlı Dam Lake

S Benzer, R Benzer, AÇ Günal - Biologia, 2017 - degruyter.com
This study aims to compare the growth estimation of narrow-clawed crayfish (Astacus
leptodactylus Eschscholtz, 1823) obtained from two methods which are length–weight …

[PDF][PDF] Alternative growth models in fisheries: Artificial Neural Networks

S Benzer, R Benzer - Journal of Fisheries, 2019 - core.ac.uk
In this study growth of Atherina boyeri, collected from Süreyyabey Dam Lake, was
determination by Artificial Neural Networks (ANNs) along with study of length weight …

[PDF][PDF] Evaluation of a new computer method (ANNs) and traditional methods (LWRS and VBGF) in the calculation of some growth parameters of two cyprinid species

EI Ozcan, O Serdar - Fresenius Environmental Bulletin, 2019 - acikerisim.aksaray.edu.tr
ABSTRACT Artificial Neural Networks (ANNs) are a very reliable computer program used in
many areas such as growth parameters. The aim of this study to compare the growth …

[PDF][PDF] New perspectives for predicting growth properties of crayfish (Astacus leptodactylus Eschscholtz, 1823) in Uluabat Lake

S Benzer, R Benzer - Pakistan Journal of Zoology, 2018 - researchgate.net
This study aims to compare the growth estimation result of the two methods which are
Length-Weight Relations and Artificial Neural Networks from Uluabat Lake regarding narrow …

Growth and length–weight relationships of Pseudorasbora parva (Temminck & Schlegel, 1846) in Hirfanlı Dam Lake: Comparison with traditional and artificial neural …

S Benzer, R BENZER - Iranian Journal of Fisheries Sciences, 2020 - jifro.areeo.ac.ir
The present study was carried out to assess the population structure and growth with length
weight relations, von Bertalanffy equations and artificial neural networks (ANNs) of topmouth …