NDLI: Identifying the degree of influential effects for the causal relationships in a Bayesian network model using group decision making technique

Content Provider	IEEE Xplore Digital Library
Author	Jongsawat, N. Premchaiswadi, W.
Copyright Year	2010
Description	Author affiliation: Graduate School of Information Technology in Business, Siam University, Bangkok, Thailand (Jongsawat, N.; Premchaiswadi, W.)
Abstract	In this paper, we propose a methodology based on group decision making for weighting expert opinions or the degree of an expert's belief in identifying influential effects from parent variables to child variables in a BN model. The methodology consists of three sequential steps. The first step is a pre-processing process where the experts need to identify and select every pair of variables that have a causal relationship between them for the BN model. All the experts in the group must agree with each other for the selections. Second, we map every pair of causal variables into alternatives. Next, experts sort the alternatives by means of a fixed set of linguistic categories; each one has associated a numerical score. We apply a method of weighting individual expert opinions in order to arrange the sequence of alternatives in each step of the decision making procedure. The sequential decision procedure is repeated until it determines a final subset of experts where all of them positively contribute to the agreement for group decision making. Lastly, we transform the alternatives and the collective scores that we obtain from previous step into the BN models. We select a simple diagnostic model of a vehicle fuel system as a case study.
Starting Page	51
Ending Page	57
File Size	368243
Page Count	7
File Format	PDF
ISBN	9781424498741
ISSN	21570981
e-ISBN	9781424498765
DOI	10.1109/ICTKE.2010.5692914
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-24
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Collective ranking Agreement measure Bayesian methods Decision making Euclidean distance Weak order Numerical models Fuels Bayesian network Collective preference Pragmatics
Content Type	Text
Resource Type	Article

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