Balıkçılık Endüstrisinde Kullanılan Büyüme Modellerinde Geleneksel Yaklaşımlar ile Yapay Sinir Ağlarının Yaklaşımlarının Karşılaştırılması
Title
Comparison of Approaches of Artificial Neural Networks and Traditional Approaches in Growth Models Used in Fisheries Industry
Abstract
In this study, traditional approaches (length-weight relationships-LWR) and artificial neural networks (ANNs) approaches
are examined in the growth models used in the fisheries industry. In our study, we used ANNs model instead of the
traditional statistical growth estimation techniques used in the fisheries industry to determine how to obtain results. The data
obtained with conventional growth models are compared with the data obtained with artificial neural networks. Data
samples were collected from Mogan Lake. During the study, 571 fish (Atherina boyeri) were caught in 2016. Artificial
Neural Networks have been shown to be an option in assessing growth characteristics. Findings of this study are important
in determining the correct estimates in fisheries management and in evaluating the growth characteristics.
Editor: H. Kemal İlter, Ankara Yıldırım Beyazıt University, Turkey
Received: August 19, 2018, Accepted: October 18, 2018, Published: November 10, 2018
Copyright: © 2018 IMISC Benzer, Benzer. This is an open-access article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.
