Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach

• Main Authors: Mohamad, Edy Tonnizam, Armaghani, Danial Jahed, Momeni, Ehsan, Nezhad Khalil Abad, Seyed Vahid Alavi
• Format: Article
• Published: Springer Verlag 2015
• Subjects: HD1394-1394.5 Real estate management
• Online Access: http://eprints.utm.my/id/eprint/55016/; http://dx.doi.org/10.1007/s10064-014-0638-0
• Institution: Universiti Teknologi Malaysia

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...