APPLICATION OF AKAIKE INFORMATION CRITERION STATISTICS TO GEOTECHNICAL INVERSE ANALYSIS - THE EXTENDED BAYESIAN METHOD

A new type of indirect inverse analysis procedure is proposed to overcome the difficulties the geotechnical inverse analyses are encountering such as unstability and nonuniqueness of the solutions as well as multicollinearity. Also, the problem of model identification is emphasized. These difficulties are eased by combining the objective information (i.e. the observation data) with the subjective information (i.e. the prior information) in an appropriate way by the so-termed extended Bayesian method. The method is based on the new view on the Bayesian model proposed by Akaike based on the Akaike Information Criterion Statistic. The criterion is also employed in the model identification in this study. A rather detailed description of Akaike's proposal on the Bayesian model is presented. A case study on an embankment on soft clay is presented to illustrate the effectiveness of the new method.