Title of article :
Growth and length–weight relationships of Pseudorasbora parva (Temminck & Schlegel, 1846) in Hirfanlı Dam Lake: Comparison with traditional and artificial neural networks approaches
Author/Authors :
Benzer S. Gazi University - Gazi Faculty of Education - Ankara, Turkey , Benzer R. National Defense University - Department of Computer Engineering - Ankara, Turkey
Abstract :
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 gudgeon fish, between May 2015 and May 2016, in the Hirfanlı
Dam Lake. The age of topmouth gudgeon caught from the Hirfanlı Dam Lake ranged
between I to V years. The von Bertalanffy growth function growth coefficient k was 0.5
and asymptotic length L∞ was 9.13 mm fork length (FL). The weight-length
relationship is given by the regression equation W=0.01275334×L3.0005 for all
individual. Growth equations in length (mm) and weight (g g) are: Lt = 9.13 [1–e–0.380 (t
+ 0.5)] and Wt = 10.36 [1–e–0.380 (t + 0.5)]3.0005 for all individual. Minimum and maximum
sizes was were 2.7 and 9.2 cm FL for all individuals. Here, we examine the growth
properties (length and weight) of topmouth gudgeon by modern (artificial neural
networks) and traditional approaches (Length weight Relations and von Bertalanffy
growth model) in the Hirfanlı Dam Lake. This study presents the first LWR, von
Bertalanffy and ANNs references for this species in the Hirfanlı Dam Lake
Keywords :
Topmouth gudgeon , Length weight relations , Artificial neural networks , Growth
Journal title :
Iranian Journal of Fisheries Sciences