摘要：Abstract This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth. Graphical abstract Display Omitted Highlights • LSSVM, ELM, and GPR successfully applied for determination of rock depth. • Equation developed for determination of rock depth. • The LSSVM, ELM and GPR yield spatial variability of rock depth.
关键词：Rock depth; Spatial variability; Least square support vector machine; Gaussian process regression; Extreme learning machine;
