2015 : Differential evolution adaptive metropolis sampling method to provide model uncertainty and model selection criteria to determine optimal model for Rayleigh wave dispersion

Dr. Sungkono S.Si, M.Si

Prof.Dr. Bagus Jaya Santosa

Ir. Sungkono CES

Abstract

The near-surface S-wave velocity is important tool for environmental studies. This parameter can be derived by inverting of Rayleigh wave dispersion. Inversion of Rayleigh wave dispersion has a nonunique solution. Thus, solving inverse problems is not only done to find the fittest model but also to characterize the uncertainty of the model result. In this paper, we applied and tested a Bayesian inversion method using a developed differential evolution adaptive metropolis (DREAM(ZS)) approach to provide posterior distribution of model parameters (PDMPs). This method consists of Markov chain Monte Carlo (MCMC) simulation method which rapidly estimates the PDMP. After obtaining the resulted posterior, we could estimate representative model (such as mean, mode, median, covariance, and percentile model, the maximum posterior model, and uncertainty model), the probability distributions for …