Dynamic Bayesian belief network
Dynamic Bayesian belief network to model the development of walking and cycling schemes
... a Bayesian belief network (BBN) has been found in many applications described in the literature (Jensen, 1996; Neil et ...a network in which arrows are pointing from parent nodes (causes) to ...
23
Online Decision Support System and Machine Learning Modeling using Bayesian Belief Network
... the Bayesian Belief Network, which would respond for the queries by supplying the known facts, partial facts, evidence, requirements ...using dynamic programming for search ...
10
Reduced complexity turbo equalization using a dynamic Bayesian network
... randomizing the occurrence of bit errors in a transmitted data block, but also to aid in the dispersion of the posi- tive feedback effect, which is due to the fact that the MAP algorithm used for equalization and decoding ...
20
Online Cleaning of Wireless Sensor Data Resulting in Improved Context Extraction
... to dynamic nature of the ...extraction. Bayesian Belief Networks are used here to quantitatively encode the dependencies among various ...for Bayesian Belief Network Construction ...
9
Multi-radio network optimisation using Bayesian belief propagation
... Fig. 9 (a) shows both the required and offered capacities for differ- ent dynamic and static assignment schemes. In general, the data rate provided by the optimised scheme closely follows the target data rate ...
5
Consequence and normative guidance
... A final remark regarding (?) is in order. In §4 we distinguished synchronic and diachronic bridge principles. As a wide scope principle, (?) is most naturally read as a synchronic principle. It states that, at any given ...
30
Modeling multiple time units delayed gene regulatory network using dynamic Bayesian network.
... on the statistical patterns hidden in the gene expression dataset. Some re searchers argue th at gene expression data does not contain enough information to construct gene regulatory network, especially for large ...
101
Unraveling temporal processes using probabilistic graphical models
... partitioned dynamic Bayesian networks for capturing distribution regime changes, benefiting from an intuitive and compact representation with the solid theoretical foundation of Bayesian ...
191
Searching Multiregression Dynamic Models of Resting-State fMRI Networks Using Integer Programming
... the dynamic Granger causal models (Havlicek et ...the dynamic of connectivity is directly estimated in LMDM, most other models consider connectivity as static or estimate only the different strengths of ...
39
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 ...
8
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 ...
5
Fault Analysis of Complex Systems via Dynamic Bayesian Network
... temporal Bayesian networks (TBNs) have alternatively been proposed to explicitly incorporate time in the modeling of sequential dependencies without resort to Markov ...a dynamic gate for the system ...
10
Reasons for (prior) belief in Bayesian epistemology
... prior beliefs as rational or appropriate, and to criticize others as irrational or at least unreasonable. Yet, we intuitively think of some prior beliefs as more reasonable than others. We tend to consider conspiracy ...
23
Reasons for (prior) belief in bayesian epistemology
... ‘good’ Bayesian priors from ‘bad’ ones – the former are sometimes required to maximize entropy, for example – but these stipulations often seem rather ad hoc and do not generally ‘ground’ an agent’s beliefs in a ...
20
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 ...
11
Application of Bayesian Networks to Integrity Management of Energy Pipelines
... A Bayesian network (BN) is a graphical acyclic diagram (DAG) representing the joint distribution of a set of random ...the Bayesian updating of a large set of random variables, BNs have become ...
161
Assessing Chemical Mixtures and Human Health: Use of Bayesian Belief Net Analysis
... a Bayesian Belief Network (BBN) [16-19] to assess the impact of individual or groups of PCB congeners on the odds of an endometriosis diagno- sis controlling for ...
7
Scaling POMDPs For Selecting Sellers in E-markets-Extended Version
... namic Bayesian Network that represents the transition and observation probabilities of the SALE POMDP: query ac- tions do not affect the actual states but only the agent’s be- liefs over the state factors, ...
16
Supply chain risk network management : a bayesian belief network and expected utility based approach for managing supply chain risks
... maker. Network theory and ISM based tools are useful in assessing the driving and dependency influence of risks (Aloini et ...risk network provides an effective visual tool to help the decision maker ...
50
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. ...
8