Soft Computing-Based Models for Predicting the Characteristic Impedance of Igneous Rock from Their Physico-mechanical Properties

Abstract Rock properties are important for design of surface and underground mines as well civil engineering projects. Among rock is the characteristic impedance rock. Characteristic plays a crucial role in solving problems shock waves mining engineering. The characteristics has been related with other literature. However, regression models between literature do not consider variabilities their characterizations. Therefore, this study proposed two soft computing [i.e., artificial neural network (ANN) adaptive neuro-fuzzy inference system (ANFIS)] better predictions igneous rocks. performances were statistically evaluated, they found to satisfactorily predict very strong statistical indices. In addition, multiple linear (MLR) was developed compared ANN ANFIS models. model best performance, followed by lastly MLR model. have Pearson's correlation coefficients close 1, indicating that can be used