Prediction of compressive and tensile strength of Gaziantep basalts via neural networks and gene expression programming

ÇANAKCI H., Baykasoglu A., GÜLLÜ H.

NEURAL COMPUTING & APPLICATIONS, cilt.18, sa.8, ss.1031-1041, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 8
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/s00521-008-0208-0
  • Dergi Adı: NEURAL COMPUTING & APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1031-1041
  • Anahtar Kelimeler: Artificial neural networks, Gene expression programming, Basalt, Tensile and compressive strength, ROCKS
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

In this paper, two soft computing approaches, which are known as artificial neural networks and Gene Expression Programming (GEP) are used in strength prediction of basalts which are collected from Gaziantep region in Turkey. The collected basalts samples are tested in the geotechnical engineering laboratory of the University of Gaziantep. The parameters, "ultrasound pulse velocity", "water absorption", "dry density", "saturated density", and "bulk density" which are experimentally determined based on the procedures given in ISRM (Rock characterisation testing and monitoring. Pergamon Press, Oxford, 1981) are used to predict "uniaxial compressive strength" and "tensile strength" of Gaziantep basalts. It is found out that neural networks are quite effective in comparison to GEP and classical regression analyses in predicting the strength of the basalts. The results obtained are also useful in characterizing the Gaziantep basalts for practical applications.