Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores

Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores

Accurate estimation of the uniaxial compressive strength (UCS) of carbonate rocks underpins safe design and stability assessment in karst-influenced geotechnical projects. This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis fu...

Full description

Saved in:
Bibliographic Details
Main Authors: Jose W. Naal-Pech, Leonardo Palemón-Arcos, Youness El Hamzaoui
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
uniaxial compressive strength
carbonate rock cores
artificial neural networks
radial basis function
Bayesian regularization
sensitivity analysis
Online Access:https://www.mdpi.com/2076-3417/15/10/5609
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/15/10/5609

Similar Items