BPNN and ANFIS models for prediction of floor bearing characteristics of weak rock foundations

Abstract

Analysis of stability (mainly bearing strength and settlement) under a footing on regularly bedded, jointed and layered model rock mass is conducted using Back Propagating Neural Network (BPNN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS). The inputs required for the modeling were imported from the laboratory results of the measurements carried out earlier [1]. Rock mass were modeled as elastic-plastic with Drucker- Prager failure criteria for plane strain condition. The results of the footing settlements and bearing strengths derived from BPNN and ANFIS models were compared with the footing settlements corresponding to the maximum applied bearing pressure on floor strata (for different sizes of footing plates and also under varying anisotropy conditions of floor strata) as obtained from the experimental results and FEM investigations and the bearing strengths obtained from the laboratory investigations. It is deduced that ANFIS model predicts accurately well vis-a-vis experimental results though the results predicted from BPNN model compares well with those of FEM analysis.