Using Bayesian network analysis to support centre of gravity analysis in military planning [An article from: European Journal of Operational Research]
Book Details
Author(s)L. Falzon
PublisherElsevier
ISBN / ASINB000RR9VOW
ISBN-13978B000RR9VO5
AvailabilityAvailable for download now
Sales Rank13,187,496
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Centre of gravity (COG) analysis is an integral and cognitively demanding aspect of military operational planning. It involves identifying the enemy and friendly COG and subsequently determining the critical vulnerabilities that have to be degraded or negated to influence the COG of each side. This paper describes a modelling framework based on the causal relationships among the critical capabilities and requirements for an operation. The framework is subsequently used as a basis for the construction, population and analysis of Bayesian networks to support a rigorous and systematic approach to COG analysis. The importance of this work is that it uses existing planning process concepts to facilitate the construction of comprehensive models in which uncertainties and subjective judgements are clearly represented, thus enabling future re-use and traceability. The visual representation of the COG causal structure helps to clarify thinking and provides a way to record and impart this thinking. Moreover, it gives planners the capability to perform impact analysis, that is, to determine which actions are most likely to achieve a desirable end-state. The paper discusses the methodology, development and implementation of the COG Network Effects Tool (COGNET) suite for model population and model checking as well as impact analysis.
Description:
Centre of gravity (COG) analysis is an integral and cognitively demanding aspect of military operational planning. It involves identifying the enemy and friendly COG and subsequently determining the critical vulnerabilities that have to be degraded or negated to influence the COG of each side. This paper describes a modelling framework based on the causal relationships among the critical capabilities and requirements for an operation. The framework is subsequently used as a basis for the construction, population and analysis of Bayesian networks to support a rigorous and systematic approach to COG analysis. The importance of this work is that it uses existing planning process concepts to facilitate the construction of comprehensive models in which uncertainties and subjective judgements are clearly represented, thus enabling future re-use and traceability. The visual representation of the COG causal structure helps to clarify thinking and provides a way to record and impart this thinking. Moreover, it gives planners the capability to perform impact analysis, that is, to determine which actions are most likely to achieve a desirable end-state. The paper discusses the methodology, development and implementation of the COG Network Effects Tool (COGNET) suite for model population and model checking as well as impact analysis.
