Multi-layered Bayesian Neural Networks for Simulation and Prediction Stress-Strain Time Series

Abstract

The aim of the paper is to investigate the differences as far as the numerical accuracy is concerned between feedforward layered Artificial Neural Networks (ANN) learned by means of Kalman filtering (KF) and ANN learned by means of the evidence procedure for Bayesian technique. The stressstrain experimental time series for concrete hysteresis loops obtained by the experiment of cyclic loading is presented as considered example.