Bayesian belief network theory
Dynamic Bayesian belief network to model the development of walking and cycling schemes
... a Bayesian belief network (BBN) theory is extended to model the influence between and within factors in the dynamic decision making ...
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Bayesian Belief Network, Bayesian Learning, Information Security, Intelligent Agent, Risk Assessment.
... the Bayesian learning theory is the best choice for this intelligent ...The Bayesian learning theory is based on conditional probability and the risk evaluation is an uncertain prediction ...
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Supply chain risk network management : a bayesian belief network and expected utility based approach for managing supply chain risks
... risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network ...of ...
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Bayesian belief network model for the safety assessment of nuclear computer-based systems
... We do not intend here to describe the theory of BBN models itself—there is an extensive existing literature on this (see e.g. [Pearl 1993, Pearl 1988, CACM 1995, Jensen 1996, Lauritzen and Spiegelhalter 1988]). We ...
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Development of a clinical decision model for thyroid nodules
... information. Bayesian networks allow clinicians to derive insights about the data domain because the networks are graphical, hierarchical representations of how conditionally independent varia- bles associate to ...
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Mobile sensor network noise reduction and recalibration using a Bayesian network
... naive Bayesian net- work to identify local outliers and detect faulty ...trained Bayesian classifier for probabilistic ...on Bayesian belief ...
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Reasons for (prior) belief in Bayesian epistemology
... beliefs, formally represented by credence orders over di¤erent epistemic possibilities. This result, which is an interpretationally new variant of an earlier theorem (Dietrich and List 2012a,b), shows that if two simple ...
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Assessing Chemical Mixtures and Human Health: Use of Bayesian Belief Net Analysis
... Methods: Bayesian Belief Network (BBN) models were developed and empirically assessed in a cohort comprising 84 women aged 18 - 40 years who underwent a laparoscopy or laparotomy between 1999 and ...
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Belief propagation and locally Bayesian learning
... Once we understand LBL as a special case of a message pass- ing algorithm in a chain-ordered factor graph, we can exper- iment with other approximations to the full Bayesian model. The consequence of the LBL ...
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Reasons for (prior) belief in bayesian epistemology
... a Bayesian update – namely a proposition picking out a subset of that re…ned set of possibilities – might then rule out more possibilities underlying some meeting points ...repeated belief changes of the ...
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Online Cleaning of Wireless Sensor Data Resulting in Improved Context Extraction
... 2.3 Domain Modeling Using Bayesian Belief Network The BBN construction algorithms discussed in section 2.1 model relationships between feature variables Cluster Ids and Time of the day, [r] ...
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Interdependency modeling of supply chain risks incorporating game theoretic risks
... Abstract – Most of the current risk quantification techniques being applied in the field of Supply Chain Risk Management consider risk factors to be independent. This research considers risks as interdependent triggers, ...
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Consequence and normative guidance
... On the other hand, some philosophers—especially (though not only) external- ists of various stripes—may find fault with the epistemological presuppositions underlying Harman’s conception of a theory of reasoning. ...
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A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c means
... 8 for new techniques and automated tools that can assist us in transforming the data into more useful information and knowledge. The classification is the task of assigning objects to one of several predefined ...
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We can believe the Error Theory
... a belief on a consideration without making at least an implicit normative judgment” ...a belief as “merely causing”, or “merely explaining” why he has a belief ...error theory would seem to be ...
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A fuzzy based Bayesian Belief Network approach for railway bridge condition monitoring and fault detection
... example, Network Rail, which is the owner of the railway network in the UK, estimates to spend 35 billion of pounds over a 5-year period for mainte- nance and renewal activities of the railway ...
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Implementation of E-Service Intelligence in the Field of Web Mining
... [3] A important aspect of web mining is the clustering of customer similar profiles to create customer “segments” [Mobasher et al., 2000].Clustered user profiles are a good option when there exist insufficient data to ...
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Collection and analysis of data for ship condition monitoring aiming at enhanced reliability and safety
... The INCASS MRA tool consists of three stages, the data acquisition and processing, the reliability model and the Decision Support System (DSS). The MRA methodology includes the gathering of data in order to process them. ...
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A Survey on MR MNBC:MAX REL based Feature Selection for the Multi Relational Bayesian Belief Network
... A Bayesian network (BN)[9] consists of a directed, acyclic graph and a probability distribution for each node in that graph given its immediate ...Bayes Network Classifier is based on a ...
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A Bayesian Belief Network for Murray Valley encephalitis virus risk assessment in Western Australia
... In this paper, we present a novel Bayesian Belief Net- work-based model for assessing Murray Valley encepha- litis virus (MVEV) risk in Western Australia. Although this application of BBNs to MVEV risk ...
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