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首页> 外文期刊>fresenius environmental bulletin >ARTIFICIAL NEURALNETW ORKS APPROACH TO GROWTH PROPERTIES A RISSO, 1810 IN YAMULA DAM LAKE, TURKEY
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ARTIFICIAL NEURALNETW ORKS APPROACH TO GROWTH PROPERTIES A RISSO, 1810 IN YAMULA DAM LAKE, TURKEY

机译:ARTIFICIAL NEURALNETW ORKS APPROACH TO GROWTH PROPERTIES A RISSO, 1810 IN YAMULA DAM LAKE, TURKEY

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摘要

It is aimed to predict of length-weight relationship (LWR) parameters by using Artificial Neural Networks (ANNs). The present study investigates the properties of the Big-scale Sand Smelt, Atherina boyeri Risso, 1810 in Yamula Dam Lake (Kayseri, Turkey). Minimum and maximum fork length size and weight were found 3.5 and 8.3 cm; 0.38 and 4.82 g for all individuals. The weight- length relationships were W = 0.01285708 L2-8167 (R2 = 0.934) for females, W = 0.00972323 L2'8690 (r2 = 0.950) for males and W=0.1014131 L2 8476 (R2 = 0.940) for all individuals. The condition factor was calculated as 0.812, 0.797 and 0.804 for females, males and all individuals respectively. The results obtained by ANNs and LWR equation are compared to those obtained by the growth rate. LWR and ANNs models was found for females, males and all individuals.

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