Investigation of patient‐sharing networks using a Bayesian network model selection approach for congruence class models

Distress Classification of Road Structures via Adaptive Bayesian Network Model Selection

Journal of Computing in Civil Engineering ◽

10.1061/(asce)cp.1943-5487.0000686 ◽

2017 ◽

Vol 31 (5) ◽

pp. 04017044 ◽

Cited By ~ 8

Author(s):

K. Maeda ◽

S. Takahashi ◽

T. Ogawa ◽

M. Haseyama

Keyword(s):

Model Selection ◽

Bayesian Network ◽

Network Model ◽

Bayesian Network Model

A two phase approach to Bayesian network model selection and comparison between the MDL and DGM scoring heuristics

SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483) ◽

10.1109/icsmc.2003.1245709 ◽

2004 ◽

Cited By ~ 2

Author(s):

M. Kane ◽

F. Sahin ◽

A. Savakis

Keyword(s):

Model Selection ◽

Bayesian Network ◽

Network Model ◽

Bayesian Network Model ◽

Two Phase ◽

Phase Approach

Empirical evaluation of scoring functions for Bayesian network model selection

BMC Bioinformatics ◽

10.1186/1471-2105-13-s15-s14 ◽

2012 ◽

Vol 13 (Suppl 15) ◽

pp. S14 ◽

Cited By ~ 26

Author(s):

Zhifa Liu ◽

Brandon Malone ◽

Changhe Yuan

Keyword(s):

Model Selection ◽

Bayesian Network ◽

Network Model ◽

Empirical Evaluation ◽

Scoring Functions ◽

Bayesian Network Model

A Hierarchical Bayesian Network Model for Flood Resilience Quantification of Housing Infrastructure Systems

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering ◽

10.1061/ajrua6.0001108 ◽

2021 ◽

Vol 7 (1) ◽

pp. 04020060

Author(s):

Mrinal Kanti Sen ◽

Subhrajit Dutta ◽

Jahir Iqbal Laskar

Keyword(s):

Bayesian Network ◽

Network Model ◽

Hierarchical Bayesian ◽

Bayesian Network Model ◽

Infrastructure Systems

ON SUITABLE MODEL SELECTION APPROACH FOR ANALYSIS OF MENTAL HEALTH SERVICE USE DATA

IAPQR TRANSACTIONS ◽

10.32381/iapqrt.2019.43.02.6 ◽

2019 ◽

Vol 43 (2) ◽

pp. 212-222

Author(s):

DULAL K. BHAUMIK ◽

◽

SUBHASH ARYAL ◽

SCOTT HUR ◽

◽

...

Keyword(s):

Mental Health ◽

Mental Health Service ◽

Model Selection ◽

Health Service ◽

Service Use ◽

Mental Health Service Use ◽

Health Service Use ◽

Suitable Model ◽

Model Selection Approach ◽

Selection Approach

A Model Selection Approach to the Two-Phase Regression Estimation and The Human Sensitivity Analysis in Urban Ecosystem

Behaviormetrika ◽

10.2333/bhmk.10.13_1 ◽

1983 ◽

Vol 10 (13) ◽

pp. 1-18

Author(s):

Masashi Itoh ◽

Kazuo Noda ◽

Yutaka Shinada ◽

Naomi Tachibana

Keyword(s):

Sensitivity Analysis ◽

Model Selection ◽

Urban Ecosystem ◽

Regression Estimation ◽

Two Phase ◽

Model Selection Approach ◽

Selection Approach

Multiple Structural Breaks in Cointegrating Regressions: A Model Selection Approach

SSRN Electronic Journal ◽

10.2139/ssrn.3489870 ◽

2019 ◽

Author(s):

Alexander Schmidt ◽

Karsten Schweikert

Keyword(s):

Model Selection ◽

Structural Breaks ◽

Multiple Structural Breaks ◽

Model Selection Approach ◽

Selection Approach

Predicting the risk of GenX contamination in private well water using a machine-learned Bayesian network model

Journal of Hazardous Materials ◽

10.1016/j.jhazmat.2021.125075 ◽

2021 ◽

pp. 125075

Author(s):

Javad Roostaei ◽

Sarah Colley ◽

Riley Mulhern ◽

Andrew A. May ◽

Jacqueline MacDonald Gibson

Keyword(s):

Bayesian Network ◽

Network Model ◽

Well Water ◽

Bayesian Network Model

Impact Mechanism of the Ecological Vulnerability of Highly Developed Islands Based on the Bayesian Network Model—Applied to the Changshan Islands

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084150 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4150

Author(s):

Keyu Qin ◽

Haijun Huang ◽

Jingya Liu ◽

Liwen Yan ◽

Yanxia Liu ◽

...

Keyword(s):

Bayesian Network ◽

Network Model ◽

Geographical Information ◽

Global Changes ◽

Bayesian Network Model ◽

Island Ecosystems ◽

Impact Mechanism ◽

The North ◽

Ecological Vulnerability ◽

The Impact

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters

Misper-Bayes: A Bayesian Network Model for Missing Person Investigations

IEEE Access ◽

10.1109/access.2021.3069081 ◽

2021 ◽

pp. 1-1

Author(s):

Denis Reilly ◽

Mark Taylor ◽

Paul Fergus ◽

Carl Chalmers ◽

Steven Thompson

Keyword(s):

Bayesian Network ◽

Network Model ◽

Bayesian Network Model