Mean squared error based on the number of neurons using Levenberg–Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms in the Multi-Layer Perceptron Artificial Neural Network (MLPANN) model for antler beam diameter and length in training dataset.
- Sunday O. Peters (413614)
- Mahmut Sinecen (6392420)
- George R. Gallagher (6392423)
- Lauren A. Pebworth (6392426)
- Suleima Jacob (6392429)
- Jason S. Hatfield (6392432)
- Kadir Kizilkaya (6392435)
Publication date
February 2019
DOI Publisher
Public Library of Science (PLoS)Abstract
Mean squared error based on the number of neurons using Levenberg–Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms in the Multi-Layer Perceptron Artificial Neural Network (MLPANN) model for antler beam diameter and length in training dataset.</p
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