Prediction of Shear Wave Velocity in Limestone by Using New Intelligent Methods

The purpose of current study is development of an intelligent model for estimation of shear wave velocity in limestone. Shear wave velocity is one of the most important rock dynamic parameters. Because rocks have complicated structure، direct determination of this parameter takes time، spends expenditure and requires accuracy. On the other hand، there are no precise equations for indirect determination of it and most of them are empirical. In this study، by using data sets of several dams of Iran adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) methods، model and equation are rendered for prediction of shear wave velocity in limestone. Totally، 170 sets of data were used for modeling. From these data sets، 136 ones were utilized for building the intelligent model، and 34 were used for their performance evaluation. Compressional wave velocity، density and porosity، were considered as input parameters. In the relevant predictions، the values of R2 and RMSE for ANFIS model were consecutively 0. 958 and 113. 620. These values for GEP equation were 0. 928 and 110. 006. Because these results have accuracy، they could be used for prediction of shear wave velocity for limestone in the future.