Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks

Author:

Momeni Ehsan,Jahed Armaghani Danial,Hajihassani Mohsen,Mohd Amin Mohd For

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference86 articles.

1. Estimating the strength of rock materials;Bieniawski;J. South Afr. Inst. Min. Metall.,1974

2. ASTM, Standard Test Method for Unconfined Compressive Strength of Intact Rock Core Specimens, American Society for Testing and Materials, D2938-95.

3. The complete ISRM suggested methods for rock characterization, testing and monitoring: 1974–2006;ISRM,2007

4. A fuzzy model to predict the unconfined compressive strength and modulus of elasticity of a problematic rock;Gokceoglu;Eng. Appl. Artif. Intell.,2004

5. Predicting of compressive and tensile strength of limestone via genetic programming;Baykasoglu;Expert Syst. Appl.,2008

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