O'Reilly logo

Benefits of Bayesian Network Models by Christophe Simon, Philippe Weber

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

3Bayesian Network: Modeling Formalism of the Structure Function of Multi-State Systems

3.1. Introduction

In the case of multi-state systems, standard dependability methods, proposed in the literature are difficult to implement [LIS 03]. In this section, the methodology previously presented in the Boolean case is transposed to multi-state systems to prove that it is easy to obtain multi-state models with BN. Methods are presented for the construction of a model of multi-state systems. The methods are based on cut-sets, tie-sets or the principle of top-down analysis based on functional analysis. Section 3.2.3 explains the functional analysis-based method and explains how it provides an easy way to build an efficient model.

3.2. BN models in the multi-state case

The first step when modeling a multi-state model for dependability analysis is to define the set of variables xi that represent the component states [SHU 10] as follows:

[3.1] eq3.1.jpg

with li being the first failure state, i.e. the component does not satisfy its functioning goals. States 1 … (li – 1) are degraded functioning states, i.e. the component is not fully functional but it does not compromise the system mission. States lini are several failure states of the component that can have different consequences on the system state.

The system state is also defined by a multi-state variable with respect to different functioning ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required