Portraying probabilistic relationships of continuous nodes in Bayesian networks with ranked nodes method

نویسندگان

چکیده

This paper advances the use of ranked nodes method (RNM) to portray probabilistic relationships continuous quantities in Bayesian networks (BNs). In RNM, are represented by with discrete ordinal scales. The quantified conditional probability tables (CPTs) generated expert-elicited parameters. When formed discretizing scales, ignorance about functioning RNM can lead discretizations that make generation sensible CPTs impossible. While a guideline exists on this matter, it is limited requirement define an equal number states for all nodes. presents two novel discretization approaches consider and allow have non-equal numbers states. first one, called “static approach”, be given any desired stay unchanged during BN. second “dynamic algorithmically updated BN help manage sizes CPTs. Both based original idea that, besides parameters, relationship defined initial RNM-compatible elicited from domain expert. Overall, new offer easier more versatile way using depict quantities. doing so, they also facilitate effective diverse BNs decision support systems.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Using Ranked nodes to model qualitative judgements in Bayesian Networks

Although Bayesian Nets (BNs) are increasingly being used to solve real world risk problems, their use is still constrained by the difficulty of constructing the node probability tables (NPTs). A key challenge is to construct relevant NPTs using the minimal amount of expert elicitation, recognising that it is rarely cost-effective to elicit complete sets of probability values. We describe a simp...

متن کامل

Generalizing Continuous Time Bayesian Networks with Immediate Nodes

An extension to Continuous Time Bayesian Networks (CTBN) called Generalized CTBN (GCTBN) is presented; the formalism allows one to model, in addition to continuous time delayed variables (with exponentially distributed transition rates), also non delayed or “immediate” variables, which act as standard chance nodes in a Bayesian Network. The usefulness of this kind of model is discussed through ...

متن کامل

Ranked nodes: A simple and effective way to model qualitative judgements in large-scale Bayesian Networks

Ranked nodes: A simple and effective way to model qualitative judgements in large-scale Bayesian Networks Norman Fenton and Martin Neil Risk Assessment and Decision Analysis Research Group Department of Computer Science, Queen Mary, University of London and Agena Ltd 21 Feb, 2005 Abstract Although Bayesian Nets (BNs) are increasingly being used to solve real world risk problems, their use is st...

متن کامل

Using Hidden Nodes in Bayesian Networks

In the construction of a Bayesian network, it is always assumed that the variables starting from the same parent are conditionally independent. In practice, this assumption may not hold, and will give rise to incorrect inferences. In cases where some dependency is found between variables, we propose that the creation of a hidden node, which in effect models the dependency, can solve the problem...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Decision Support Systems

سال: 2022

ISSN: ['1873-5797', '0167-9236']

DOI: https://doi.org/10.1016/j.dss.2021.113709