Estimation of California bearing ratio by using soft computing systems

This publication has 23 references indexed in Scilit:

• Prediction of artificial soil’s unconfined compression strength test using statistical analyses and artificial neural networks
  Advances in Engineering Software, 2010
• Evaluating the strength and deformability properties of Misis fault breccia using artificial neural networks
  Expert Systems with Applications, 2009
• Compaction Behaviour and Prediction of its Characteristics of Fine Grained Soils with Particular Reference to Compaction Energy
  Soils and Foundations, 2004
• Using neural networks to predict workability of concrete incorporating metakaolin and fly ash
  Advances in Engineering Software, 2003
• Prediction of compaction characteristics of fine-grained soils
  Géotechnique, 2002
• On the applicability of neural networks for soil dynamic amplification analysis
  Soil Dynamics and Earthquake Engineering, 2001
• Neural network design for engineering applications
  Computers & Structures, 2001
• Concrete strength prediction by means of neural network
  Construction and Building Materials, 1997
• On the identification of compaction characteristics by neuronets
  Computers and Geotechnics, 1996
• Ohio's Typical Moisture-Density Curves
  1959