ResearchSpace

Validation & verification of a Bayesian network model for aircraft vulnerability

Show simple item record

dc.contributor.author Schietekat, Sunelle
dc.contributor.author De Waal, Alta
dc.contributor.author Gopaul, Kevin G
dc.date.accessioned 2017-06-07T07:58:12Z
dc.date.available 2017-06-07T07:58:12Z
dc.date.issued 2016-09
dc.identifier.citation Schietekat, S., De Waal, A. and Gopaul, K.G. 2016. Validation & verification of a Bayesian network model for aircraft vulnerability. 12th INCOSE SA Systems Engineering Conference, 12-14 September 2016, CSIR International Convention Centre, Pretoria, South Africa en_US
dc.identifier.isbn 978-0-620-72719-8
dc.identifier.uri http://incose.org.za/pubs/2016/Papers/INCOSE_SA_2016_paper_7.pdf
dc.identifier.uri http://hdl.handle.net/10204/9209
dc.description 12th INCOSE SA Systems Engineering Conference, 12-14 September 2016, CSIR International Convention Centre, Pretoria, South Africa en_US
dc.description.abstract This paper provides a methodology for Validation and Verification (V&V) of a Bayesian Network (BN) model for aircraft vulnerability against Infrared (IR) missile threats. The model considers that the aircraft vulnerability depends both on a missile’s performance as well as the doctrine governing the missile’s launch. The model is a Knowledge Based System (KBS) and therefore has a knowledge base which consists of both expert knowledge and simulated data which acts as input to the model and is used during inferencing to understand how variables interact. A widely accepted process to certify that a model is suitable for use is the Verification, Validation and Accreditation (VV&A) procedure and is followed in this paper. Throughout the V&V procedure, similarities are drawn between this VV&A process and the well-known Vee-model. en_US
dc.language.iso en en_US
dc.publisher INCOSE en_US
dc.relation.ispartofseries Worklist;17622
dc.subject Validation en_US
dc.subject Verification en_US
dc.subject Bayesian Networks en_US
dc.subject Knowledge based systems en_US
dc.subject Aircraft vulnerability en_US
dc.subject Infrared en_US
dc.subject Inferencing en_US
dc.subject 12th INCOSE SA Systems Engineering Conference 2016 en_US
dc.title Validation & verification of a Bayesian network model for aircraft vulnerability en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Schietekat, S., De Waal, A., & Gopaul, K. G. (2016). Validation & verification of a Bayesian network model for aircraft vulnerability. INCOSE. http://hdl.handle.net/10204/9209 en_ZA
dc.identifier.chicagocitation Schietekat, Sunelle, Alta De Waal, and Kevin G Gopaul. "Validation & verification of a Bayesian network model for aircraft vulnerability." (2016): http://hdl.handle.net/10204/9209 en_ZA
dc.identifier.vancouvercitation Schietekat S, De Waal A, Gopaul KG, Validation & verification of a Bayesian network model for aircraft vulnerability; INCOSE; 2016. http://hdl.handle.net/10204/9209 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Schietekat, Sunelle AU - De Waal, Alta AU - Gopaul, Kevin G AB - This paper provides a methodology for Validation and Verification (V&V) of a Bayesian Network (BN) model for aircraft vulnerability against Infrared (IR) missile threats. The model considers that the aircraft vulnerability depends both on a missile’s performance as well as the doctrine governing the missile’s launch. The model is a Knowledge Based System (KBS) and therefore has a knowledge base which consists of both expert knowledge and simulated data which acts as input to the model and is used during inferencing to understand how variables interact. A widely accepted process to certify that a model is suitable for use is the Verification, Validation and Accreditation (VV&A) procedure and is followed in this paper. Throughout the V&V procedure, similarities are drawn between this VV&A process and the well-known Vee-model. DA - 2016-09 DB - ResearchSpace DP - CSIR KW - Validation KW - Verification KW - Bayesian Networks KW - Knowledge based systems KW - Aircraft vulnerability KW - Infrared KW - Inferencing KW - 12th INCOSE SA Systems Engineering Conference 2016 LK - https://researchspace.csir.co.za PY - 2016 SM - 978-0-620-72719-8 T1 - Validation & verification of a Bayesian network model for aircraft vulnerability TI - Validation & verification of a Bayesian network model for aircraft vulnerability UR - http://hdl.handle.net/10204/9209 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record