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Relational Dynamic Bayesian Networks

S. Sanghai, P. Domingos, D. Weld
<span title="2005-12-02">2005</span> <i title="AI Access Foundation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4ax4efcwajcgvidb6hcg6mwx4a" style="color: black;">The Journal of Artificial Intelligence Research</a> </i> &nbsp;
In this paper, we introduce relational dynamic Bayesian networks (RDBNs), which are an extension of dynamic Bayesian networks (DBNs) to first-order logic.  ...  Modeled as dynamic Bayesian networks, these processes have discrete variables with very large domains and extremely high dimensionality.  ...  Dynamic Bayesian Networks Dynamic Bayesian Networks (DBNs) (Dean & Kanazawa, 1989) are an extension of Bayesian networks for modeling dynamic systems.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.1625">doi:10.1613/jair.1625</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/67szhdojard5xhheej5pw7ovuq">fatcat:67szhdojard5xhheej5pw7ovuq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812184453/https://homes.cs.washington.edu/~weld/papers/sanghai-jair05.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d3/73/d3735a44c5dce249e749bda01238493bf7c9235c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.1625"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Modeling and Inference with Relational Dynamic Bayesian Networks [chapter]

Cristina Manfredotti
<span title="">2009</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
of the objects in the Domain, their attributes and their relations Relational State = State of instantiations (s i ) + State of relations (s r ) A parenthesis 9 Bayesian Networks: • Encode  ...  Intra-slice distribution: sensor model Inter-slice distribution: transition model Inference Under Markov assumption Bayesian Filter algorithm: Belief: bel(s t ) = p(s t |z 1:t ) Relations in  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-01818-3_44">doi:10.1007/978-3-642-01818-3_44</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k626yrxouzbbbjgjdhvzte2t6m">fatcat:k626yrxouzbbbjgjdhvzte2t6m</a> </span>
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Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air quality [article]

Khadija Tijani (CSTB, LIG Laboratoire d'Informatique de Grenoble, G-SCOP), Stephane Ploix, Julie Dugdale (LIG Laboratoire d'Informatique de Grenoble), Quoc Dung Ngo
<span title="2016-05-19">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper proposes a new general approach based on Bayesian networks to model the human behaviour.  ...  This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations.  ...  Fig.1 Elements of a Bayesian Network: (a) Dynamic BN (b) Different probability distributions Fig. 2 2 Elements of the model Figure 3 - 3 The dynamic Bayesian network (DBN) structure Figure 4 DBN structure  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1605.05966v1">arXiv:1605.05966v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2mu4h3vhgfewvfhef2ng7slfji">fatcat:2mu4h3vhgfewvfhef2ng7slfji</a> </span>
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Relational Dynamic Bayesian Network Modeling for Uncertainty Quantification and Propagation in Airline Disruption Management [article]

Kolawole Ogunsina, Marios Papamichalis, Daniel DeLaurentis
<span title="2022-03-23">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We employ the UTFM to assess two independent and separately disrupted flight legs from the airline route network.  ...  Acknowledgement The authors would like to thank Blair Reeves, Chien Yu Chen, Kevin Wiecek, Jeff Agold, Dave Harrington, Rick Dalton, and Phil Beck, at Southwest Airlines Network Operations Control (SWA-NOC  ...  dynamic Bayesian network architecture.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2102.05147v3">arXiv:2102.05147v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vbfhlwdb6vbexmvo7ihjervc2e">fatcat:vbfhlwdb6vbexmvo7ihjervc2e</a> </span>
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Research on Unmanned Underwater Vehicle Threat Assessment

Hongfei Yao, Hongjian Wang, Yiming Li, Ying Wang, Chunsong Han
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
In this paper, a method based on dynamic Bayesian network modeling was proposed to evaluate the UUV in an underwater threat situation.  ...  Setting up the static Bayesian network involved the addition of state transition probability and establishment of the model for assessing the dynamic Bayesian threat situation.  ...  See Fig.8 for the dynamic Bayesian model used to assess the platform-related threats.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2891940">doi:10.1109/access.2019.2891940</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/csmta7qafjdxrogfa7m53tjr34">fatcat:csmta7qafjdxrogfa7m53tjr34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429071604/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08611187.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/05/09/0509f849ea7071a95456a9fa285803260a9c271f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2891940"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Proposing the Deep Dynamic Bayesian Network as a Future Computer Based Medical System

Caoimhe M. Carbery, Adele H. Marshall, Roger Woods
<span title="">2016</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qrxicfzd5jcahil6pr67l466ju" style="color: black;">2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)</a> </i> &nbsp;
The new network will be defined as a deep dynamic Bayesian network (DDBN).  ...  Dynamic Bayesian network Dynamic Bayesian networks (DBNs) will be investigated in such a way to discover how the inclusion of a dynamic component allows the network to model real-world systems.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cbms.2016.70">doi:10.1109/cbms.2016.70</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cbms/CarberyMW16.html">dblp:conf/cbms/CarberyMW16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tj5ny5zhl5b6fduycinbmwh35i">fatcat:tj5ny5zhl5b6fduycinbmwh35i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428154054/https://pure.qub.ac.uk/portal/files/120612159/CaoimheCarbery_Skyline_CBMS2016.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/16/72/16729ec3c86536a54799067d2e553ac2249149b4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cbms.2016.70"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data [chapter]

SunYong Kim, Seiy Imoto, Satoru Miyano
<span title="">2003</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We propose a dynamic Bayesian network and nonparametric regression model for constructing a gene network from time series microarray gene expression data.  ...  The proposed method can overcome a shortcoming of the Bayesian network model in the sense of the construction of cyclic regulations.  ...  Dynamic Bayesian networks overcome this problem (see Fig. 1 ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/3-540-36481-1_9">doi:10.1007/3-540-36481-1_9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uctlwyfd2rb2xeq6mijvxy72mm">fatcat:uctlwyfd2rb2xeq6mijvxy72mm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20141114074610/http://bonsai.hgc.jp:80/~imoto/kim_biosystems2004.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0f/9c/0f9c42af10c9fff2ee1f4a8c208e172598b243a4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/3-540-36481-1_9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data

Sunyong Kim, Seiya Imoto, Satoru Miyano
<span title="">2004</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dbxvzia7tzcdzoff4xmqtr4qrq" style="color: black;">Biosystems (Amsterdam. Print)</a> </i> &nbsp;
We propose a dynamic Bayesian network and nonparametric regression model for constructing a gene network from time series microarray gene expression data.  ...  The proposed method can overcome a shortcoming of the Bayesian network model in the sense of the construction of cyclic regulations.  ...  Dynamic Bayesian networks overcome this problem (see Fig. 1 ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.biosystems.2004.03.004">doi:10.1016/j.biosystems.2004.03.004</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/15245804">pmid:15245804</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zt37upcupfew3or4fw3ily7nam">fatcat:zt37upcupfew3or4fw3ily7nam</a> </span>
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A fuzzy analytic hierarchy attribute weighting and deep learning for improving CHD prediction of optimized semi parametric extended dynamic bayesian network

K. Gomathi, D. Shanmuga Priyaa
<span title="2017-12-21">2017</span> <i title="Science Publishing Corporation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/piy2nrvrjrfcfoz5nmre6zwa4i" style="color: black;">International Journal of Engineering &amp; Technology</a> </i> &nbsp;
One among them was Extended Dynamic Bayesian Network (EDBN) which integrates temporal abstractions with DBN.  ...  Then EDBN was extended as Optimized Semi parametric Extended Dynamic Bayesian Network (OSEDBN) to handle Complex temporal abstractions in irregular interval time series data.  ...  Dynamic bayesian network The dynamic Bayesian networks (DBNs) is explored how the inclusion of dynamic components access the network to model the real world system.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14419/ijet.v7i1.1.9274">doi:10.14419/ijet.v7i1.1.9274</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2rl3cv4etrf2njaczjrk2fo3ea">fatcat:2rl3cv4etrf2njaczjrk2fo3ea</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719201250/https://www.sciencepubco.com/index.php/ijet/article/download/9274/3202" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c2/fa/c2fa5e704243759a1e9f0ce91b20fe001cc6435e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14419/ijet.v7i1.1.9274"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Network Information Security Situation Assessment Based on Bayesian Network

Wang Xing-zhu
<span title="2016-05-31">2016</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4h7flaxsjnh6he3qbiwvxbekxe" style="color: black;">International Journal of Security and Its Applications</a> </i> &nbsp;
The simulation results are compared with that of static Bayesian network model. The experimental results show that this method can better reflect the dynamic changes of network space operations.  ...  In this situation, the situation of the system is based on Fuzzy Dynamic Bayesian network. The model of situation awareness and situation estimation is constructed.  ...  Dynamic Bayesian Network Structure Dynamic Bayesian Network Inference Algorithm The dynamic Bias network inference algorithm is derived from the formula (1) Bias formula: ( ) ( ) () ( ) ( ) x p yx p  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijsia.2016.10.5.12">doi:10.14257/ijsia.2016.10.5.12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6xrd2ob245b3viu4hqtzcwxmy4">fatcat:6xrd2ob245b3viu4hqtzcwxmy4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602172317/http://www.sersc.org/journals/IJSIA/vol10_no5_2016/12.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3b/0f/3b0fd38b93290f323bb6e07aa436d71e91b70c56.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijsia.2016.10.5.12"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Dynamic Bayesian Network and Nonparametric Regression Model for Inferring Gene Networks

Sun Yong Kim, Seiya Imoto, Satoru Miyano
<span title="">2002</span> <i title="Japanese Society for Bioinformatics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jf2bmhtlzjh4zjrkh3rivxd2sq" style="color: black;">Genome Informatics Series</a> </i> &nbsp;
Introduction A Bayesian network is a powerful tool for modeling relations among a large number of random variables .  ...  For a solution of this problem , in this paper, we propose a dynamic Bayesian network and nonparametric regression model for estimating a gene network with cyclic regulations from time series microarray  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11234/gi1990.13.371">doi:10.11234/gi1990.13.371</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xdrdklmqpjgajgnswxsrlakkra">fatcat:xdrdklmqpjgajgnswxsrlakkra</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220507124006/https://www.jstage.jst.go.jp/article/gi1990/13/0/13_0_371/_pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f2/5c/f25c54c0b0622c0ffd0b03c19fd5f9e677bd707b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11234/gi1990.13.371"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

INFORMATION SECURITY RISK ASSESSMENT UNDER UNCERTAINTY USING DYNAMIC BAYESIAN NETWORKS

R. Sarala .
<span title="2014-05-25">2014</span> <i title="eSAT Publishing House"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m4rdj3kwwfcbvfzkv6kcnagwtm" style="color: black;">International Journal of Research in Engineering and Technology</a> </i> &nbsp;
The Dynamic Bayesian Network models help to detect the uncertain relationship associated with the risk event.  ...  In this paper, a novel approach is presented; where Dynamic Bayesian Network models are constructed to identify multi stage attacks.  ...  A Dynamic Bayesian Network is made up with related time slices of fixed Bayesian networks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15623/ijret.2014.0319055">doi:10.15623/ijret.2014.0319055</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2ofmvrw53jectoeyng3u7oypya">fatcat:2ofmvrw53jectoeyng3u7oypya</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813081603/http://esatjournals.net/ijret/2014v03/i19/IJRET20140319055.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/02/c4/02c4b0ce22b5c0222e9e2e1c6352a490217daba3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15623/ijret.2014.0319055"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

The Joint Framework for Dynamic Topic Semantic Link Network Prediction

Anping Zhao, Lingling Zhao, Yu Yu
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
INDEX TERMS Semantic link network, Bayesian network, Gaussian mixture models.  ...  The proposed framework joints the Gaussian mixture model and the Bayesian network to conduct inference and prediction of topic relationships of dynamic topic semantic link network.  ...  We showed how a joint framework of the Gaussian mixture model and a Bayesian network approach are related to relationship dynamics at the topic level.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2018.2889993">doi:10.1109/access.2018.2889993</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dpqh5aducffwbi6ni44jrvrozi">fatcat:dpqh5aducffwbi6ni44jrvrozi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201108073319/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08590797.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b0/2b/b02bb64a0d1a7a737ba0d22342485a7010453f06.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2018.2889993"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Application of Spectrum Data Management Based on Bayesian Network

Dai Li
<span title="2015-07-31">2015</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cjfkr6nrjbcjrhn6a6mvtme4ay" style="color: black;">International Journal of u- and e- Service, Science and Technology</a> </i> &nbsp;
In the spectral data management, under different regions and different time, spectral data is very big, resulting in the spectrum management would be difficult, this article based on Bayesian network of  ...  , so as to realize the network reconstruction in short time.  ...  Thus, it needs to use the concepts of fuzzy sets to establish the related concepts of Bayesian networks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijunesst.2015.8.7.02">doi:10.14257/ijunesst.2015.8.7.02</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gh3fvyvrgzd5jgab462teajhfu">fatcat:gh3fvyvrgzd5jgab462teajhfu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602063334/http://www.sersc.org/journals/IJUNESST/vol8_no7/2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2f/8e/2f8e2e7d0bfcea98fcabb42f7b4c6076b557bcf3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijunesst.2015.8.7.02"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Estimating uncertainty in respondent-driven sampling using a tree bootstrap method

Aaron J. Baraff, Tyler H. McCormick, Adrian E. Raftery
<span title="2016-12-07">2016</span> <i title="Proceedings of the National Academy of Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nvtuoas5pbdsllkntnhizy4f4q" style="color: black;">Proceedings of the National Academy of Sciences of the United States of America</a> </i> &nbsp;
"Bayesian modeling for a Generalized Social Relations Model," American Psychological Association Conference on Dyadic Data 2007.  ...  Latent structure models for social networks using Aggregated Relational Data," New England Statistics Symposium 2011.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1073/pnas.1617258113">doi:10.1073/pnas.1617258113</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27930328">pmid:27930328</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5187726/">pmcid:PMC5187726</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cynagpljkfcjbm7p5mkerdter4">fatcat:cynagpljkfcjbm7p5mkerdter4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170517021606/http://www.stat.washington.edu:80/~tylermc/mccormick_cv.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c0/6c/c06c05a56880033bd0e05b49bf299758d10951d2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1073/pnas.1617258113"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5187726" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
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