Among the Markov chain Monte Carlo methods, the Gibbs sampler has the advantage that it samples from the conditional distributions
for each unknown parameter, thus decomposing the sample space. In the case the conditional distributions are not tractable,
the Gibbs sampler by means of sampling-importance-resampling is presented here. It uses the prior density function of a Bayesian
analysis as the importance sampling distribution. This leads to a fast convergence of the Gibbs sampler as demonstrated by
the smoothing with preserving the edges of 3D images of emission tomography. 相似文献
Simulated annealing (SA) is being increasingly used for the generation of stochastic models of spatial phenomena because of its flexibility to integrate data of diverse types and scales. The major shortcoming of SA is the extensive CPU requirements. We present a perturbation mechanism that significantly improves the CPU speed. Two conventional perturbation mechanisms are to (1) randomly select two locations and swap their attribute values, or (2) visit a randomly selected location and draw a new value from the global histogram. The proposed perturbation mechanism is a modification of option 2: each candidate value is drawn from a local conditional distribution built with a template of kriging weights rather than from the global distribution. This results in accepting more perturbations and in perturbations that improve the variogram reproduction for short scale lags. We document the new method, the increased convergence speed, and the improved variogram reproduction. Implementation details of the method such as the size of the local neighborhood are considered.相似文献
Stability conditions in an area located NW of Barcelona (Spain) are discussed. Here, several mass movements were observed, mainly affecting weathered Paleozoic slates. Many of these failures involved slopes cut along recent infrastructures: debris flows, wedge and plane failures, generally surficial, occurred more frequently. After a detailed geological and geomorphologic survey, geomechanic characterization was carried out, according to RMR and SMR classifications. This rating gave a prediction of slope behaviour, in fairly good agreement with the real observed one.
Stability numerical analysis was carried out for the main cut slopes, based upon the Limit Equilibrium Method. First of all, the deterministic factor of safety was computed using the mean values of parameters. After that, a simulation technique based upon the Monte Carlo Method was applied in order to obtain factor of safety distributions. The probability of failure was estimated as P(F<1).
Finally, results from deterministic and probabilistic approaches were compared. The effectiveness of different possible remedial measures was highlighted by means of a sensitivity analysis, which showed that the more important parameters in the study area are the geometrical ones (height, slope and failure plane angles). The final technical solutions adopted are briefly outlined. 相似文献
Rainfall–runoff models with different conceptual structures for the hydrological processes can be calibrated to effectively reproduce the hydrographs of the total runoff, while resulting in water budget components that are essentially different. This finding poses an open question on the reliability of rainfall–runoff models in reproducing hydrological components other than those used for calibration. In an effort to address this question, we use data from the Glafkos catchment in western Greece to calibrate and compare the ENNS model, a research-oriented lumped model developed for the river Enns in Austria developed for the river Enns in Austria, with the operational MIKE SHE model. Model performance is assessed in the light of the conceptual/structural differences of the modelled hydrological processes, using indices calculated independently for each year, rather than for the whole calibration period, since the former are stricter. We show that even small differences in the representation of hydrological processes may impact considerably on the water budget components that are not measured (i.e. not used for model calibration). From all water budget components, direct runoff exhibits the highest sensitivity to structural differences and related model parameters.