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Abstract
Bayesian Networks (BN) are efficient to represent knowledge and for the reasoning in uncertainty. However the classic BN requires manual definition of the network structure by an expert, who also defines the values entered into the conditional probability tables. In practice, it can be time-consuming, hence the article proposes the use of Learning Bayesian Networks (LBN). The aim of the study is not only to present LBN, which can be helpful in civil engineering problems, but also to analyze and evaluate the potential of a selected software. Based on a real example the functional values of the Open Markov, Hugin and AgenaRisk applications were compared.
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
MATEC Web of Conferences
no. 219,
pages 1 - 8,
ISSN: 2261-236X - Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Siemaszko A., Apollo M.: Application possibilities of LBN for civil engineering issues// MATEC Web of Conferences -Vol. 219, (2018), s.1-8
- DOI:
- Digital Object Identifier (open in new tab) 10.1051/matecconf/201821904008
- Bibliography: test
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- OpenMarkov Tutorial -Version 0.2.0 (2017) open in new tab
- A. Hanson: Hugin Tutorial (2015) open in new tab
- AgenaRisk 7.0 User Manual, Agena Ltd, (2016) open in new tab
- M. W. Kembłowski, B. Grzyl, A. Kristowski, A. Siemaszko, Procedia Eng. 196 (2017) open in new tab
- Verified by:
- Gdańsk University of Technology
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