Abstract
Most of the inverse problems encountered in geotechnical inverse analysis are illposed, thus some type of regularization procedure need to be applied. In this presentation, several regularization procedures are compared through a simple problem, a laterally loaded pile (2.4m long) in homogeneous sand in a laboratory pit. The regularization procedures employed are the minimum norm solution based on the singular value decomposition, Kitagawa's solution, L curve method and the extended Bayesian method (EBM) with ABIC (Akaike Bayesian Information Criterion). The obtained solutions are compared with the maximum likelihood solution (ML), and characteristic of each type of solution is discussed. Furthermore, the observation noise of different levels are applied to the original data to see the change of solutions for each method. The EMB showed superiority to other types of regularization procedure in a sense it automatically accomplished the best matching between the observation data and the prior information.
