Abstract:

In order to solve the problem of geotechnical parameters distribution inferring on the condition of small sample and get over the inevitable shortcoming of subjective randomness in those fusion methods based on expert’s experience, the notion of K-L information distance in the information field was introduced; and multi-source information fusion method was proposed on the basis of the credibility of prior distributions. Using K-L information distance as a measurement of distances between parameter distributions, “the rate of prior distribution difference” was defined and the fusion weight was determined. Further, the posterior distribution was obtained by using the Bayes principle; and the fitting probability models of geotechnical parameters were optimized. It is shown in the process of a project case that the method suggested is simple while no subjective factors are included in the statistical inference. The results show that the variance of the suggested fusion distribution is smaller than ones of the existing results, which illuminates that an optimum fitting probabilistic model for parameters in statistical sense can be resulted from the proposed method; and it provides a reference for choosing design values of geotechnical parameters reasonably.

Key words: K-L information distance, multi-source information, fusion weight, Bayes principle