Predictive performance of MARS, RF, ANN and ALM types.

Predictive performance of MARS, RF, ANN and ALM types.

<p>Predictive performance of MARS, RF, ANN and ALM types.</p>

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Bibliographic Details
Main Author:	Halit Tutar (20678455) (author)
Other Authors:	Senol Celik (4697440) (author), Hasan Er (20678458) (author), Erdal Gönülal (20678461) (author)
Published:	2025
Subjects:	Biotechnology Science Policy Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified relative absolution error mean square error fresh herbage yield experimental results show artificial neural networks 69 kg da descriptive statistical values model fit statistics relative feed value div >< p data mining methods 2 </ sup lowest values suitable model best model stem diameter sd ratio respectively ), prediction performances prediction abilities plant height morphological traits konya province irrigation levels including coefficient good alternative fitted models 991 ). 22 cm 11 %, 03 mm
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