Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach
Many studies have shown that artificial neural networks (ANNs) are useful for predicting the unconfined compressive strength (UCS) of rocks. However, ANNs do have some deficiencies: they can get trapped in local minima and they have a slow learning rate. It is widely accepted that optimization algor...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
Springer Verlag
2015
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/55016/ http://eprints.utm.my/55016/ http://eprints.utm.my/55016/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|