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
Pages :
13
From page :
1098
To page :
1110
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
Serial Year :
2020
Record number :
2527074
Link To Document :
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