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Hybrid Probabilistic Relational Models for System Quality Analysis

机译:系统质量分析的混合概率关系模型

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The formalism Probabilistic Relational Models (PRM) couples discrete Bayesian Networks with a modeling formalism similar to UML class diagrams and has been used for architecture analysis. PRMs are well-suited to perform architecture analysis with respect to system qualities since they support both modeling and analysis within the same formalism. A particular strength of PRMs is the ability to perform meaningful analysis of domains where there is a high level of uncertainty, as is often the case when performing system quality analysis. However, the use of discrete Bayesian networks in PRMs complicates the analysis of continuous phenomena. The main contribution of this paper is the Hybrid Probabilistic Relational Models (HPRM) formalism which extends PRMs to enable continuous analysis thus extending the applicability for architecture analysis and especially for trade-off analysis of system qualities. HPRMs use hybrid Bayesian networks which allow combinations of discrete and continuous variables. In addition to presenting the HPRM formalism, the paper contains an example which details the use of HPRMs for architecture trade-off analysis.
机译:形式主义概率关系模型(PRM)将离散的贝叶斯网络与类似于UML类图的建模形式主义结合在一起,并已用于体系结构分析。 PRM非常适合执行有关系统质量的体系结构分析,因为它们在同一形式主义中支持建模和分析。 PRM的特殊优势是能够对不确定性很高的域执行有意义的分析,这在执行系统质量分析时通常是常见的情况。但是,在PRM中使用离散贝叶斯网络会使连续现象的分析变得复杂。本文的主要贡献是混合概率关系模型(HPRM)形式主义,它扩展了PRM以实现连续分析,从而扩展了体系结构分析的适用性,尤其是系统质量的权衡分析。 HPRM使用混合贝叶斯网络,该网络允许离散变量和连续变量的组合。除了介绍HPRM形式主义之外,本文还包含一个示例,详细说明了将HPRM用于架构折衷分析的情况。

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