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.