Number of the records: 1
Knowledge Elicitation Via Extension of Fragmental Knowledge Pieces
- 1.0328657 - ÚTIA 2010 RIV HU eng C - Conference Paper (international conference)
Kárný, Miroslav
Knowledge Elicitation Via Extension of Fragmental Knowledge Pieces.
[Získávání znalosti založené na rozšíření zlomkové znalosti.]
Proceedings of the European Control Conference 2009. Budapest: European Union Control Association, 2009, s. 1571-1575. ISBN 978-963-311-369-1.
[European Control Conference 2009. Budapest (HU), 23.08.2009-26.08.2009]
R&D Projects: GA ČR GA102/08/0567
Institutional research plan: CEZ:AV0Z10750506
Keywords : knowledge elicitation * Bayesian paradigm
Subject RIV: BB - Applied Statistics, Operational Research
http://library.utia.cas.cz/separaty/2009/AS/karny-knowledge elicitation via extension of fragmental knowledge pieces.pdf
The paper describes an advanced methodology of automatic knowledge elicitation. It merges fragmental uncertain knowledge pieces into the prior distribution of unknown parameter of a probabilistic model of a dynamic system. Careful knowledge elicitation helps in achieving as bump-less start of model-based controllers as possible. It is also important when observed data are poorly informative, which is a typical situation in closed control loops. Rigorous use of the Bayesian paradigm to the knowledge elicitation forms the essence of the methodology. Unlike former solutions, it can handle fragmental and incompletely compatible knowledge pieces in a systematic way. The description of the methodology dominates the paper and just an illustrative example is presented.
Článek popisuje pokročilou metodologii automatického získávání znalostí. Kombinuje dílčí, neurčité a zlomkové znalosti do apriorní distribuce popisující neznámý parametr pravděpodobnostního modelu dynamického systému.
Permanent Link: http://hdl.handle.net/11104/0174924
Number of the records: 1