Proposed algorithms for bayesian networks based on fuzzy set theory

摘要: Scope and method of study. Bayesian networks are directed acyclic graphs in which the nodes represent propositions, an arcs signify direct dependencies between linked strengths these quantified by conditional probabilities. Pearl (1986) developed algorithms for impart impact on to entire network via a local propagation time proportional longest path network. This study proposed use linguistic probability instead probability. Thus, this attempts develop approaches problems occurring due adoption A simulation model is employed determining type operations performed probabilities approach approximation proposed. Findings conclusions. The can be treated as either fuzzy number or set. An experiment based indicates that number. result supports position taken researchers including Bonissone Decker (1986). shows among four features representing each probability, skewness not good feature, but other such first-moment, power, entropy features.