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Exploring Localization in Bayesian Networks for Large Expert Systems [article]

Yang Xiang, David L. Poole, Michael P. Beddoes
2013 arXiv   pre-print
Current Bayesian net representations do not consider structure in the domain and include all variables in a homogeneous network.  ...  This paper presents multiply sectioned Bayesian networks that enable a (localization preserving) representation of natural subdomains by separate Bayesian subnets.  ...  Acknowled g ements This work is supported by Operating Grants A3290, OGP0044121 and OGP0090307 from NSERC, and CRD3474 from the Centre for Systems Science at SFU.  ... 
arXiv:1303.5438v1 fatcat:tldx2a2ll5bbpnhdqbynelzxsm

Exploring Localization In Bayesian Networks For Large Expert Systems [chapter]

Yang Xiang, David Poole, Michael P. Beddoes
1992 Uncertainty in Artificial Intelligence  
Current Bayesian net representations do not consider structure in the domain and include all variables in a homogeneous network.  ...  This paper presents multiply sectioned Bayesian networks that enable a (localization preserving) representation of natural subdomains by separate Bayesian subnets.  ...  Acknowledgements This work is supported by Operating Grants A3290, OGPOO44121 and OGP0090307 from NSERC, and CRD3474 from the Centre for Systems Science at SFU.  ... 
doi:10.1016/b978-1-4832-8287-9.50052-9 fatcat:jk7quua6k5fb3jtxvicecmmzfu

WiseR: An end-to-end structure learning and deployment framework for causal graphical models [article]

Shubham Maheshwari, Khushbu Pahwa, Tavpritesh Sethi
2021 arXiv   pre-print
We present wiseR, an open source application for learning, evaluating and deploying robust causal graphical models using graph neural networks and Bayesian networks.  ...  We demonstrate the utility of this application through application on for biomarker discovery in a COVID-19 clinical dataset.  ...  We are also thankful to Anant Mittal for testing the application and providing suggestions. Awasthi, Raghav, Prachi Patel, Vineet Joshi, Shama Karkal, and Tavpritesh Sethi. 2020 References  ... 
arXiv:2108.07046v2 fatcat:e5mnptvy65cd3j7kaa3alamela

Expert modelling [chapter]

Stuart Kininmonth, Steven Gray, Kasper Kok
2021 The Routledge Handbook of Research Methods for Social-Ecological Systems  
Acknowledgements We particularly want to thank Andrew Byekwaso for conducting the questionnaires, and Dennis Twinomugisha for assistance with the field programme outlined in the Kininmonth et al. (2017  ...  In this chapter, we choose to focus on just two expert methods routinely used in understanding social-ecological systems (SES): Bayesian networks (also referred to as Bayesian belief networks, decision  ...  Bayesian networks are a method to combine the correlation probability between elements in a system using the simplicity of a network model (see Chapter 23).  ... 
doi:10.4324/9781003021339-20 fatcat:uos2dlqkxndbzmfn5qhe7bkedy

Multiply sectioned Bayesian networks for neuromuscular diagnosis

Yang Xiang, B. Pant, A. Eisen, M.P. Beddoes, D. Poole
1993 Artificial Intelligence in Medicine  
In the area of neuromuscular diagnosis, several (prototype) expert systems have appeared since the early 1980's: LOCALIZE 4] for localization of peripheral nerve lesions; MYOSYS 23] for diagnosing mono-and  ...  One exception in the above systems to rule-based structure is MUNIN which is based on Bayesian networks for its uncertain reasoning component.  ...  Acknowledgements This work is supported by Operating Grants A3290, OGP0044121, OGP0090307 from NSERC, and CRD3474 from the Centre for Systems Science at Simon Fraser University.  ... 
doi:10.1016/0933-3657(93)90019-y pmid:8220685 fatcat:gshoatxernho3henmifu6qiwdq

An Infinite Multivariate Categorical Mixture Model for Self-Diagnosis of Telecommunication Networks

Amine Echraibi, Joachim Flocon-Cholet, Stephane Gosselin, Sandrine Vaton
2020 2020 23rd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)  
Expert systems, supervised machine learning, or Bayesian networks require expensive and time consuming data labeling or processing by experts.  ...  a real-world expert Bayesian Network (section 4). • We also demonstrate the clustering performance of the model on real operational data acquired from the Fixed Access Network and the Local Area Network  ...  M ost o f the considered technical solutions rely either on rule based expert systems or hand crafted expert Bayesian networks [1] - [3] .  ... 
doi:10.1109/icin48450.2020.9059491 dblp:conf/icin/EchraibiFGV20 fatcat:qtuid6a4zjgupjgubpykrqdohu

Multi-focus and multi-window techniques for interactive network exploration

Priya Krishnan Sundarararajan, Ole J. Mengshoel, Ted Selker, Pak Chung Wong, David L. Kao, Ming C. Hao, Chaomei Chen, Christopher G. Healey
2013 Visualization and Data Analysis 2013  
We demonstrate our technique by showing how it supports interactive debugging of a Bayesian network model of an electrical power system.  ...  In addition, we show that it can simplify visual analysis of an electrical power network as well as a medical Bayesian network.  ...  ACKNOWLEDGMENTS This material is based, in part, upon work supported by NSF grants CCF-0937044 and ECCS-0931978.  ... 
doi:10.1117/12.2005659 dblp:conf/vda/SundarararajanM13 fatcat:rfoui53cxbff5isbmd7gw6qzrm

A Bayesian network to manage risks of maritime piracy against offshore oil fields

Amal Bouejla, Xavier Chaze, Franck Guarnieri, Aldo Napoli
2014 Safety Science  
The potential of Bayesian networks is used to manage this large number of parameters and identify appropriate counter-measures.  ...  In recent years, pirate attacks against shipping and oil field installations have become more frequent and more serious.  ...  The use of dynamic Bayesian networks is a way to explore.  ... 
doi:10.1016/j.ssci.2014.04.010 fatcat:t6abtysuvrghlgw5quvigiya2e

Evaluation of Bayesian networks for modelling habitat suitability and management of a protected area

Sarah J. Douglas, Adrian C. Newton
2014 Journal for Nature Conservation  
Bayesian networks were constructed on the basis of the scientific literature and expert knowledge, and were then tested using results from a field survey.  ...  Here we examine the use of Bayesian networks to support the management of protected areas, through the development of habitat suitability models for eight species of conservation concern.  ...  Acknowledgements Many thanks to all of the experts who contributed to this project, including A. Byfield, C. Chatters, G. Read, A. Barker, L. Barker, P. Brock, P. Brock, N. Brouwers, P. Budd, G.  ... 
doi:10.1016/j.jnc.2014.01.004 fatcat:cdn2ddu24zdmdk4hwurbtfywtq

Information Security Risk Assessment of Smartphones using Bayesian Networks

Kristian Herland, Heikki H�mm�inen, Pekka Kekolahti
2016 Journal of Cyber Security and Mobility  
This study comprises an information security risk assessment of smartphone use in Finland using Bayesian networks.  ...  The risks, consequences, probabilities and impacts are identified from domain experts in a 2-stage interview process with 8 experts as well as from existing research and statistics.  ...  Further research is also warranted for developing more effective tools and methods for expert elicitation and consolidation of results to be used in Bayesian networks.  ... 
doi:10.13052/jcsm2245-1439.424 fatcat:g446fbjblfbfzabn5sxrodoavu

Network Engineering for Complex Belief Networks [article]

Suzanne M. Mahoney, Kathryn Blackmond Laskey
2013 arXiv   pre-print
Methods for evaluating complex belief network models are discussed. The ideas are illustrated with examples from a large belief network construction problem in the military intelligence domain.  ...  Like any large system development effort, the construction of a complex belief network model requires systems engineering to manage the design and construction process.  ...  Beddoes ( 1 992), Exploring Systems: Networks of Pfm1sible Inference Morgan Localization In Bayesian Networks For Large Expert Kaufmann, San Mateo, CA.  ... 
arXiv:1302.3591v1 fatcat:gjq5e34sd5blxn6mz5suvmpiei

A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR

Magnus Moglia, Kim S. Alexander, Manithaythip Thephavanh, Phomma Thammavong, Viengkham Sodahak, Bountom Khounsy, Sysavanh Vorlasan, Silva Larson, John Connell, Peter Case
2018 Agricultural Systems  
Highlights  A Bayesian Network was built to explore the chances of practice change amongst farmers.  The focus of the study is smallholder farmers in southern Lao PDR.  The model emphasizes systemic  ...  Abstract A Bayesian Network model has been developed that synthesizes findings from concurrent multidisciplinary research activities.  ...  Acknowledgments Research reported in this paper was funded by the Australian Centre for International Agricultural  ... 
doi:10.1016/j.agsy.2018.04.004 fatcat:tff3thypezb3xcwk2366cxnxnm

Applications of Bayesian Networks

Ron S. Kenett
2019 Transactions on machine learning and data mining  
Modelling relationships between variables has been a major challenge for statisticians in a wide range of application areas.  ...  Bayesian Networks (BN) combine graphical analysis with Bayesian analysis to represent relations linking measured and target variables.  ...  In conclusion, this paper aims to show that Bayesian Networks offer unique opportunities for statisticians to work collaboratively with content experts in a wide range of application domains and in addressing  ... 
dblp:journals/mldm/Kenett19 fatcat:bdbu54tdkbfxthuzmp6yvogdpm

Applications of Bayesian Networks

Ron S. Kenett
2012 Social Science Research Network  
Modelling cause and effect relationships has been a major challenge for statisticians in a wide range of application areas.  ...  Bayesian Networks (BN) combine graphical analysis with Bayesian analysis to represent causality maps linking measured and target variables.  ...  In conclusion, we suggest that Bayesian Networks offer unique opportunities for statisticians to work collaboratively with content experts in a wide range of application domains.  ... 
doi:10.2139/ssrn.2172713 fatcat:smqyixwfjneslpcgetiztktj7e

Fault Localization for Self-Managing Based on Bayesian Network
베이지안 네트워크 기반에 자가관리를 위한 결함 지역화

Shun-Shan Piao, Jeong-Min Park, Eun-Seok Lee
2008 The KIPS Transactions PartB  
In this paper, we propose fault localization for self-managing in performance evaluation in order to improve system reliability via learning and analyzing real-time streams of system performance events  ...  The selected node ordering lists will be used in network modeling, and hence improving learning efficiency.  ...  Conclusion In this paper, an approach to fault localization using Bayesian network for self-managing is proposed especially in performance evaluation domain for improving system reliability.  ... 
doi:10.3745/kipstb.2008.15-b.2.137 fatcat:4vfeorqh5verdkbfciy5qcww7m
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