Unlike earlier studies, Gregory used a branch of statistics called Bayesian analysis.
与较早的研究不同的是，格列格雷运用了统计学的一种方法——贝叶斯过滤分析法。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
A software project risk analysis process based on Bayesian networks is presented in this paper.
论文提出了一种基于贝叶斯网络的软件项目风险分析过程。
A novel clustering algorithm based on Bayesian model was introduced into the analysis of large-scale gene expression profiles.
在大规模基因表达谱的数据分析中引入了一种全新的基于贝叶斯模型的聚类算法。
A new dynamic fault tree analysis method based on discrete-time Bayesian networks is proposed.
提出了一种基于离散时间贝叶斯网络的动态故障树分析方法。
The paper presents a Bayesian networks(BN) framework for the reliability analysis of phased-mission systems(PMS), named PMS-BN model.
针对多阶段系统（PMS）的可靠性评估问题，提出了一种基于贝叶斯网络（BN）的可靠性分析模型PMS-BN。
Due to the difficulty of multi-state fault tree analysis, a new method based on Bayesian networks is proposed by means of an example of multi-state radar system.
针对多态系统故障树分析的难点，通过一个多态雷达系统的实例给出了一种基于贝叶斯网络的多态故障树分析方法。
Through the analysis of Bayesian net's applicability in computer network security evaluation, this paper presents a novel method to evaluate network security.
通过分析贝叶斯网络在计算机网络安全评估中的适用性，提出了一种新的网络安全评估方法。
Fifthly, A risk analysis implementation flow based on Bayesian Networks(BNs) for risk analysis module is presented. In addition, the BNs is applied to risk analysis module of a real case.
第五，针对风险分析模块提出了一种基于贝叶斯网络的风险分析方法及其实现过程，并利用实际案例说明贝叶斯网络在软件项目风险分析过程中的应用过程。
We used a Bayesian approach (a contrast-based network meta-analysis method) for indirect analyses and presented the results as posterior median relative risk with 95% credibility intervals.
我们对间接分析采用贝氏方法(以对比为基础的网络统合分析方法)，且以事后中位数相对风险95%贝氏可靠区间来表示结果。
We used a Bayesian approach (a contrast-based network meta-analysis method) for indirect analyses and presented the results as posterior median relative risk with 95% credibility intervals.
我们对间接分析采用贝氏方法(以对比为基础的网络统合分析方法)，且以事后中位数相对风险95%贝氏可靠区间来表示结果。
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