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...
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Main Authors: | , , , |
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Format: | Article |
Published: |
Springer Verlag
2015
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/55016/ http://dx.doi.org/10.1007/s10064-014-0638-0 |
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Institution: | Universiti Teknologi Malaysia |