The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models wer...The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.展开更多
Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification techniq...Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.展开更多
The initiative of internet-based virtual computing environment （iVCE） aims to provide the end users and applications with a harmonions, trustworthy and transparent integrated computing environment which will facilit...The initiative of internet-based virtual computing environment （iVCE） aims to provide the end users and applications with a harmonions, trustworthy and transparent integrated computing environment which will facilitate sharing and collaborating of network resources between applications. Trust management is an elementary component for iVCE. The uncertain and dynamic characteristics of iVCE necessitate the requirement for the trust management to be subjective, historical evidence based and context dependent. This paper presents a Bayesian analysis-based trust model, which aims to secure the active agents for selecting appropriate trusted services in iVCE. Simulations are made to analyze the properties of the trust model which show that the subjective prior information influences trust evaluation a lot and the model stimulates positive interactions.展开更多
An existing Bayesian flood frequency analysis method is applied to quantile estimation for Pearson type three (P-III) probability distribution. The method couples prior and sample information under the framework of Ba...An existing Bayesian flood frequency analysis method is applied to quantile estimation for Pearson type three (P-III) probability distribution. The method couples prior and sample information under the framework of Bayesian formula, and the Markov Chain Monte Carlo (MCMC) sampling approach is used to estimate posterior distributions of parameters. Different from the original sampling algorithm (i.e. the important sampling) used in the existing approach, we use the adaptive metropolis (AM) sampling technique to generate a large number of parameter sets from Bayesian parameter posterior distributions in this paper. Consequently, the sampling distributions for quantiles or the hydrological design values are constructed. The sampling distributions of quantiles are estimated as the Bayesian method can provide not only various kinds of point estimators for quantiles, e.g. the expectation estimator, but also quantitative evaluation on uncertainties of these point estimators. Therefore, the Bayesian method brings more useful information to hydrological frequency analysis. As an example, the flood extreme sample series at a gauge are used to demonstrate the procedure of application.展开更多
This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posterior...This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posteriors under these priors is validated.Two sampling algorithms are introduced to compute the posteriors.A simulation study is conducted to investigate the performance of the objective Bayesian procedure.Finally,the authors apply the approach to a degradation data.展开更多
基金the National Natural Science Foundation of China(No.12072290).
文摘The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.
基金Projects(41362015,51164012) supported by the National Natural Science Foundation of ChinaProject(2012AA061901) supported by the National High-tech Research and Development Program of China
文摘Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
基金The National Basic Research 973 Program of China (No2005CB321804)
文摘The initiative of internet-based virtual computing environment （iVCE） aims to provide the end users and applications with a harmonions, trustworthy and transparent integrated computing environment which will facilitate sharing and collaborating of network resources between applications. Trust management is an elementary component for iVCE. The uncertain and dynamic characteristics of iVCE necessitate the requirement for the trust management to be subjective, historical evidence based and context dependent. This paper presents a Bayesian analysis-based trust model, which aims to secure the active agents for selecting appropriate trusted services in iVCE. Simulations are made to analyze the properties of the trust model which show that the subjective prior information influences trust evaluation a lot and the model stimulates positive interactions.
基金supported by the National Basic Research Pro-gram of China ("973" Program) (Grant No. 2007CB714104)the National Natural Science Foundation of China (Grant No. 50779013)
文摘An existing Bayesian flood frequency analysis method is applied to quantile estimation for Pearson type three (P-III) probability distribution. The method couples prior and sample information under the framework of Bayesian formula, and the Markov Chain Monte Carlo (MCMC) sampling approach is used to estimate posterior distributions of parameters. Different from the original sampling algorithm (i.e. the important sampling) used in the existing approach, we use the adaptive metropolis (AM) sampling technique to generate a large number of parameter sets from Bayesian parameter posterior distributions in this paper. Consequently, the sampling distributions for quantiles or the hydrological design values are constructed. The sampling distributions of quantiles are estimated as the Bayesian method can provide not only various kinds of point estimators for quantiles, e.g. the expectation estimator, but also quantitative evaluation on uncertainties of these point estimators. Therefore, the Bayesian method brings more useful information to hydrological frequency analysis. As an example, the flood extreme sample series at a gauge are used to demonstrate the procedure of application.
基金supported by the National Natural Science Foundation of China under Grant Nos.11201005,11526070 and 11601008the Project of National Bureau of Statistics under Grant No.2013LZ17+1 种基金the Project of Anhui Educational Committee under Grant No.gxfx ZD2016015the Natural Science Foundation of Anhui Province under Grant No.1408085MA07
文摘This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posteriors under these priors is validated.Two sampling algorithms are introduced to compute the posteriors.A simulation study is conducted to investigate the performance of the objective Bayesian procedure.Finally,the authors apply the approach to a degradation data.
