Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5516

Title: Combining morphological analysis and Bayesian Networks for strategic decision support
Authors: De Waal, AJ
Ritchey, T
Keywords: Morphological analysis
Bayesian networks
Strategic decision support
Issue Date: Dec-2007
Publisher: Operations Research Society of South Africa (ORSSA)
Citation: De Waal, AJ and Ritchey, T. 2007. Combining morphological analysis and Bayesian Networks for strategic decision support. ORiON: Journal of the Operational Research Society of South Africa, Vol 23(2), pp 105-121
Abstract: Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative and quantitative part. The qualitative part is a cause-and-effect, or causal graph. The quantitative part depicts the strength of the causal relationships between variables. Combining MA and BN, as two phases in a modelling process, allows us to gain the benefits of both of these methods. The strength of MA lies in defining, linking and internally evaluating the parameters of problem spaces and BN modelling allows for the definition and quantification of causal relationships between variables. This paper gives a short presentation of MA and BN and discusses how these two computer aided methods can be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support.
Description: Copyright: 2007 Operations Research Society of South Africa (ORSSA)
URI: http://hdl.handle.net/10204/5516
ISSN: 0529-191X
Appears in Collections:Human language technologies
Logistics and quantitative methods
General science, engineering & technology

Files in This Item:

File Description SizeFormat
De Waal_2007.pdf442.17 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback