提出了仿真可信度评估网(CENS,Credibility Evaluation Net for Simulation)的方法,建立了网的数学定义和原理,给出了网的图示、性质和计算方法.为了进一步反映专家在评估中的不确定性,更真实地评价仿真系统的可信度,将模糊综合评价法...提出了仿真可信度评估网(CENS,Credibility Evaluation Net for Simulation)的方法,建立了网的数学定义和原理,给出了网的图示、性质和计算方法.为了进一步反映专家在评估中的不确定性,更真实地评价仿真系统的可信度,将模糊综合评价法应用于CENS.在介绍了模糊综合评价原理的基础上,建立了模糊CENS体系,提出了模糊CENS的计算方法和使用步骤,并给出了1个仿真可信度评估的应用实例.展开更多
Track theory rested on the foundation of the radial distribution of dose from δ rays as the central contribution of atomic physics to heavy ion radiobiology.Here,a new calculation of the radial distribution of dose i...Track theory rested on the foundation of the radial distribution of dose from δ rays as the central contribution of atomic physics to heavy ion radiobiology.Here,a new calculation of the radial distribution of dose is applied, in which the classical angular distribution of dose of delta rays and a logarithmic polynomial representation of the electron range-energy relation are used,to form the basis of the present thindown calculation.Calculations of inactivation cross sections for heavy ions in the track width regime displaying thindown for E.Colt B/r and Bs-1,and for Bacillus Subtilus are straightforward for these are 1-hit detectors,Calculations for V-79 hamster cells are more complex.They follow the original development of this model for eucaryotic cells,and make use of the cross sections calculated for hypothetical internal targets which are then asserted to be proportional to the measured cellular inactivation cross sections.The results are in reasonable agreement with experimental data.展开更多
The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situ...The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situations where the objects of interest are not constantly monitored. Thus events are known only to have occurred between the two observation periods. Interval censoring has become increasingly common in the areas that produce failure time data. This paper explores the statistical analysis of interval-censored failure time data with applications. Three different data sets, namely Breast Cancer, Hemophilia, and AIDS data were used to illustrate the methods during this study. Both parametric and nonparametric methods of analysis are carried out in this study. Theory and methodology of fitted models for the interval-censored data are described. Fitting of parametric and non-parametric models to three real data sets are considered. Results derived from different methods are presented and also compared.展开更多
文摘提出了仿真可信度评估网(CENS,Credibility Evaluation Net for Simulation)的方法,建立了网的数学定义和原理,给出了网的图示、性质和计算方法.为了进一步反映专家在评估中的不确定性,更真实地评价仿真系统的可信度,将模糊综合评价法应用于CENS.在介绍了模糊综合评价原理的基础上,建立了模糊CENS体系,提出了模糊CENS的计算方法和使用步骤,并给出了1个仿真可信度评估的应用实例.
文摘Track theory rested on the foundation of the radial distribution of dose from δ rays as the central contribution of atomic physics to heavy ion radiobiology.Here,a new calculation of the radial distribution of dose is applied, in which the classical angular distribution of dose of delta rays and a logarithmic polynomial representation of the electron range-energy relation are used,to form the basis of the present thindown calculation.Calculations of inactivation cross sections for heavy ions in the track width regime displaying thindown for E.Colt B/r and Bs-1,and for Bacillus Subtilus are straightforward for these are 1-hit detectors,Calculations for V-79 hamster cells are more complex.They follow the original development of this model for eucaryotic cells,and make use of the cross sections calculated for hypothetical internal targets which are then asserted to be proportional to the measured cellular inactivation cross sections.The results are in reasonable agreement with experimental data.
文摘The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situations where the objects of interest are not constantly monitored. Thus events are known only to have occurred between the two observation periods. Interval censoring has become increasingly common in the areas that produce failure time data. This paper explores the statistical analysis of interval-censored failure time data with applications. Three different data sets, namely Breast Cancer, Hemophilia, and AIDS data were used to illustrate the methods during this study. Both parametric and nonparametric methods of analysis are carried out in this study. Theory and methodology of fitted models for the interval-censored data are described. Fitting of parametric and non-parametric models to three real data sets are considered. Results derived from different methods are presented and also compared.
