dc.contributor.author |
Schietekat, Sunelle
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|
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 |
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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 -
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en_ZA |