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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/10/5609 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|