Abstract
In this study, based on compiled numerical-experimental datasets, important variables, including porosity, density, compressional and shear wave velocity, were utilised to develop a novel model for predicting coal permeability with high accuracy. Multiple linear regression, response surface methodology and gene expression programming were employed to develop empirical models based on the foregoing variables. The performance of the developed models was evaluated using statistical indices. The results showed that the GEP-based model has the best prediction performance compared with other techniques. The proposed GEP-based model with its explicit structure can be readily used in practical applications by field engineers.
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