scholarly journals Virtual evidence transmission algorithm preserving the global consistency property of algebraic Bayesian networks

2014 ◽  
Vol 3 (26) ◽  
pp. 204
Author(s):  
Konstantin Vladislavovich Frolenkov
Keyword(s):  
Bayesian Networks ◽  
Global Consistency ◽  
Consistency Property

TOPOLOGICAL CONSTRAINTS FOR SENSE OF DIRECTION

1998 ◽  
Vol 09 (02) ◽  
pp. 179-197 ◽  
Author(s):  
PAOLA FLOCCHINI ◽  
NICOLA SANTORO
Keyword(s):  
Interconnection Networks ◽  
Communication Complexity ◽  
Local Orientation ◽  
Forbidden Subgraphs ◽  
Topological Constraints ◽  
Sense Of Direction ◽  
Global Consistency ◽  
Consistency Property ◽  
Consistency Constraints ◽  
The Relationship

In a distributed system, each entity has a label (port number) associated to each of its neighbors. It is well known that if the labeling satisfies a global consistency property called Sense of Direction, the communication complexity of many distributed problem can be greatly reduced. This property is assumed to be present and it is implicitly used in most interconnection networks. In this paper we investigate the nature of the relationship between Sense of Direction and network topology. We first consider the class of labelings which only satisfy the requirement of local orientation; that is, at each node, the outgoing edges have distinct labels. We then consider the class of labelings which also satisfy edge symmetry; that is, there exists a correlation between the labels neighbors give to their connecting edge. This class includes most of used labelings. We completely characterize the interplay between topological constraints and consistency constraints for these two classes of labelings. In fact, for each class, we identify both the set of forbidden subgraphs and the set of feasible graphs, and we show that the characterization is complete.

Bayesian Networks Based Reliability Analysis of Phased-Mission Systems

2009 ◽  
Vol 31 (10) ◽  
pp. 1814-1825 ◽  
Author(s):  
Dong LIU ◽  
Chun-Yuan ZHANG ◽  
Wei-Yan XING ◽  
Rui LI
Keyword(s):  
Bayesian Networks ◽  
Reliability Analysis

Quantifying Systemic Risk Using Bayesian Networks

2020 ◽  
Author(s):  
Sumit Sourabh ◽  
Markus Hofer ◽  
Drona Kandhai
Keyword(s):  
Bayesian Networks ◽  
Systemic Risk

The impact of subway operation on urban traffic: A GRA-BNs based study

2021 ◽  
pp. 1-16
Author(s):  
Lixin Yan ◽  
Tao Zeng ◽  
Yubing Xiong ◽  
Zhenyun Li ◽  
Qingmei Liu
Keyword(s):  
Bayesian Networks ◽  
Operating Characteristic ◽  
Urban Traffic ◽  
Relational Analysis ◽  
Traffic Security ◽  
Structural Network ◽  
Random Decision Forest ◽  
Roc Area ◽  
Grey Relational ◽  
The Impact

With the development of urbanization, urban traffic has exposed many problems. To study the subway’s influence on urban traffic, this paper collects data on traffic indicators in Nanchang from 2008 to 2018. The research is carried out from three aspects: traffic accessibility, green traffic, and traffic security. First, Grey Relational Analysis is used to select 18 traffic indicators correlated with the subway from 22 traffic indicators. Second, the data is discretized and learned based on Bayesian Networks to construct the structural network of the subway’s influence. Third, to verify the reliability of using GRA and the effectiveness of Bayesian Networks (GRA-BNs), Bayesian Networks with full indicators analysis and other four algorithms (Naive Bayes, Random Decision Forest, Logistic and regression) are employed for comparison. Moreover, the receiver operating characteristic (ROC) area, true positive (TP) rate, false positive (FP) rate, precision, recall, F-measure, and accuracy are utilized for comparing each situation. The result shows that GRA-BNs is the most effective model to study the impact of the subway’s operation on urban traffic. Then, the dependence relations between the subway and each index are analyzed by the conditional probability tables (CPTs). Finally, according to the analysis, some suggestions are put forward.

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