Zobrazeno 1 - 10
of 732
pro vyhledávání: '"Bayesian programming"'
Publikováno v:
Наукові вісті КПІ; № 4 (2021); 7-18
KPI Science News; No. 4 (2021); 7-18
Научные вести КПИ; № 4 (2021); 7-18
KPI Science News; No. 4 (2021); 7-18
Научные вести КПИ; № 4 (2021); 7-18
Background. Financial as well as many other types of risks are inherent to all types of human activities. The problem isto construct adequate mathematical description for the formal representation of risks selected and to use it for possibleloss esti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=scientific_p::aebb945b0838a610ac74d68188a2e4ae
http://scinews.kpi.ua/article/view/251684
http://scinews.kpi.ua/article/view/251684
Autor:
Anton V. Kvasnov
Publikováno v:
IET Radar, Sonar & Navigation. 14:1175-1182
This study considers the Bayesian programming methodology for recognition and classification of radio emission sources. A mathematical model of Bayesian programming proposes forming a family of probability distributions based on known parameters cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f5d47ede3a205c234fea7745c4a2e5e
https://doi.org/10.1049/iet-rsn.2019.0380
https://doi.org/10.1049/iet-rsn.2019.0380
Autor:
Yongqun He, Zuoshuang Xiang
Publikováno v:
Bayesian Network
In this chapter, we have introduced in details the miniTUBA system, and how to apply the miniTUBA dynamic Bayesian network (DBN) approach to analyze a typical use case in the areas of host-pathogen interactions using high throughput microarray data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0055cf8bf93af2c49ef75250d32ac2d9
http://www.intechopen.com/articles/show/title/minituba-a-web-based-dynamic-bayesian-network-analysis-system-
http://www.intechopen.com/articles/show/title/minituba-a-web-based-dynamic-bayesian-network-analysis-system-
Autor:
Lovejoy, William S.
Publikováno v:
Operations Research, 1991 Jan 01. 39(1), 162-175.
Externí odkaz:
https://www.jstor.org/stable/171496
Autor:
Filippo Massari
This paper examines the implications of the market selection hypothesis on the accuracy of the probabilities implied by equilibrium prices and on the “learning” mechanism of markets. I use the standard machinery of dynamic general equilibrium mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55a50bb724deea118200cc1893af722c
https://hdl.handle.net/11585/847659
https://hdl.handle.net/11585/847659
Autor:
Luis Enrique Sucar
Publikováno v:
Probabilistic Graphical Models ISBN: 9783030619428
Probabilistic Graphical Models ISBN: 9781447166986
Probabilistic Graphical Models ISBN: 9781447166986
This chapter gives an introduction to learning Bayesian networks including both parameter and structure learning. Parameter learning includes how to handle uncertainty in the parameters and missing data; it also includes the basic discretization tech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6c073bda419a959aee1803e3d6e0177
https://doi.org/10.1007/978-3-030-61943-5_8
https://doi.org/10.1007/978-3-030-61943-5_8
Publikováno v:
Neurocomputing. 258:30-40
Bayesian networks have been successfully applied to various tasks for probabilistic reasoning and causal modeling. One major challenge in the application of Bayesian networks is to learn the Bayesian network structures from data. In this paper, we ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cea7cc35398a1b6df736e3cb2494c2cf
https://doi.org/10.1016/j.neucom.2017.01.092
https://doi.org/10.1016/j.neucom.2017.01.092
Autor:
Yanjun Ma, Biao Huang
Publikováno v:
IEEE Transactions on Industrial Electronics. 64:7171-7180
Data-driven techniques such as principal component analysis (PCA) have been widely used to derive predictive models from historical data and applied for quality prediction in industry. Motivated by reducing data collinearity and extracting informativ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1257b802c170f3edaedff631c2719de5
https://doi.org/10.1109/tie.2017.2688970
https://doi.org/10.1109/tie.2017.2688970
Autor:
Edward Susko
Publikováno v:
Canadian Journal of Statistics. 45:290-309
With the advent of simulation-based methods to obtain samples from posteriors and due to increases in computational power, Bayesian methods are increasingly applied to complex problems, sometimes providing the only available methods where likelihood
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::760977d1d4875c6cda80682e891504dc
https://doi.org/10.1002/cjs.11325
https://doi.org/10.1002/cjs.11325
Publikováno v:
Computer-Aided Civil and Infrastructure Engineering. 32:820-835
Some probabilistic safety assessment models based on Bayesian networks have been recommended recently for safety analysis of highways and roads. These methods provide a very natural and powerful alternative to traditional approaches, such as fault an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d00803f46e98241b7dc20c40373a3ab0
https://doi.org/10.1111/mice.12294
https://doi.org/10.1111/mice.12294