Determination of Electrical Resistivity of Soil Based on Thermal Resistivity Using RVM and MPMR

Abstract

This article adopts Relevance Vector Machine (RVM) and Minimax Probability Machine Regression (MPMR) for prediction Soil Electrical Resistivity(R_E) of soil. RVM uses an improper hierarchical prior. It optimizes over hyperparameters. MPMR is a probabilistic model. Two models (MODEL I and MODEL II) have been adopted. Percentage sum of the gravel and sand size fractions (F) and Soil Thermal Resistivity(R_T) has been takes as inputs in MODEL I. MODEL II uses F,R_T and saturation of soils(S) as input variables. The results of RVM and MPMR have  been compared with the Artificial Neural Network (ANN). The developed RVM and MPMR proves his ability for prediction of RE of soil.