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|Title: ||Case-based situation awareness.|
|Authors: ||Nwiabu, Nuka D.|
Allison, Ian K.
|Keywords: ||Situation awareness|
|Issue Date: ||2012|
|Citation: ||NWIABU, N., ALLISON, I., HOLT, P., LOWIT, P. and OYENEYIN, B., 2012. Case-based situation awareness. In: IEEE Multi-disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support. 6-8 March 2012. Piscataway, New Jersey: IEEE. Pp. 22-29.|
|Abstract: ||Situation-aware case-based decision support
(SACBDS) systems comprise two distinct parts: situation
awareness (SA) and case-based reasoning (CBR). The SA
part keeps a finite history of the time space information
of the domain and uses rules to interpret cues from the
environment with respect to an individual user’s context,
and then anticipates future situations by performing statistical
inference over historical data. The CBR part is
the part that seeks to accomplish a particular task with
knowledge of the environment from the SA component.
This paper discusses the fusion of the CBR model and the
SA model into a case-based situation awareness (CBSA)
model for situation awareness based on experience rather
than rule, similarity assessment and problem solving prediction.
The CBSA system perceives the users’ context
and the environment and uses them to understand the
current situation by retrieving similar past situations.
Every past situation has a history. The future of a new
situation (case) is predicted through knowledge of the
history of a similar past situation. The paper evaluates the
concept in the flow assurance control domain to predict the
formation of hydrate in sub-sea oil and gas pipelines. The
results provided the CBSA system with greater number of
accurate predictions than the SACBDS system.|
|Appears in Collections:||Conference publications (Computing)|
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