De Waal, AJRitchey, T2012-01-192012-01-192007-12De 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 105-1210529-191Xhttp://hdl.handle.net/10204/5516Copyright: 2007 Operations Research Society of South Africa (ORSSA)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.enMorphological analysisBayesian networksStrategic decision supportArticleDe Waal, A., & Ritchey, T. (2007). Combining morphological analysis and Bayesian Networks for strategic decision support. http://hdl.handle.net/10204/5516De Waal, AJ, and T Ritchey "Combining morphological analysis and Bayesian Networks for strategic decision support." (2007) http://hdl.handle.net/10204/5516De Waal A, Ritchey T. Combining morphological analysis and Bayesian Networks for strategic decision support. 2007; http://hdl.handle.net/10204/5516.TY - Article AU - De Waal, AJ AU - Ritchey, T AB - 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. DA - 2007-12 DB - ResearchSpace DP - CSIR KW - Morphological analysis KW - Bayesian networks KW - Strategic decision support LK - https://researchspace.csir.co.za PY - 2007 SM - 0529-191X T1 - Combining morphological analysis and Bayesian Networks for strategic decision support TI - Combining morphological analysis and Bayesian Networks for strategic decision support UR - http://hdl.handle.net/10204/5516 ER -