Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/72335
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dc.titleGrid-enabled bayesian network
dc.contributor.authorZeng, Y.-F.
dc.contributor.authorLiu, G.-Q.
dc.contributor.authorPoh, K.-L.
dc.date.accessioned2014-06-19T04:53:46Z
dc.date.available2014-06-19T04:53:46Z
dc.date.issued2005
dc.identifier.citationZeng, Y.-F.,Liu, G.-Q.,Poh, K.-L. (2005). Grid-enabled bayesian network. AAAI Spring Symposium - Technical Report SS-05-02 : 121-126. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/72335
dc.description.abstractBayesian network has been a successful tool in the decision support systems. In the changing world, the decision making demands adaptive Bayesian methods that are composed of Bayesian inferential and learning approaches. To achieve this goal, we propose a kind of grid-enabled Bayesian networks that intend to gridify Bayesian inferential and learning methods when the advanced grid computing techniques are integrated. Most of our effort is put into the discussion of grid-enabled learning methods and grid-enabled inferential methods as well as their challenging work on the integration. It is argued that grid-enabled Bayesian networks are able to utilize all available resources to support the adaptive decision making in the changing world. Copyright © 2002, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.sourcetitleAAAI Spring Symposium - Technical Report
dc.description.volumeSS-05-02
dc.description.page121-126
dc.identifier.isiutNOT_IN_WOS
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