Indirect estimation of uniaxial compressive strength (UCS) of rocks using ANFIS techniqus

The accurate measurement of geoengineering properties of intact rock such as uniaxial compressive strength (UCS) using laboratory methods requires a lot of time and cost. Hence, development of predictive relationships and models to estimate the UCS of rocks seems to be essential in rock engineering. This study deals with the prediction of uniaxial compressive strength of sandstones using an adaptive neuro-fuzzy inference system (ANFIS) model. For this purpose, ۱۳۰ core samples were cored and comprehensive laboratory tests have been done on them. The data included porosity, P-wave velocity, dry density, slake durability index, and water absorption as input parameters and UCS as the output parameter. The performance of the proposed ANFIS model is evaluated based on the criteria including correlation coefficient (r), root mean squared error (RMSE), and variance account for (VAF). The prepared ANFIS model showed a good performance in predicting UCS with R, RMSE, and VAF values of ۰.۹۵۴, ۰.۰۷۰, and ۹۷.۰۰%, respectively.

Keywords:

Uniaxial compressive strength , Modulus of elasticity , ANFIS , Sandstone