scholarly journals Parameter learning but not structure learning: A Bayesian network model of constraints on early perceptual learning

10.1167/7.1.4 ◽  
2007 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Melchi M. Michel ◽  
Robert A. Jacobs
Keyword(s):  
Bayesian Network ◽  
Perceptual Learning ◽  
Network Model ◽  
Structure Learning ◽  
Parameter Learning ◽  
Bayesian Network Model

scholarly journals Analyzing the Effects of the Dwelling Characteristics on Space Heating Costs with the Rank Correlation Bayesian Network Model

2021 ◽  
Author(s):  
Volkan Sevinç
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Network Model ◽  
Building Materials ◽  
Structure Learning ◽  
Rank Correlation ◽  
Space Heating ◽  
Bayesian Network Model ◽  
Heating Systems ◽  
External Wall

Abstract Energy is one of the main concerns of humanity because energy resources are limited and costly. In order to reduce the costs and to use the energy for space heating effectively, new building materials, techniques and insulations facilities are being developed. Therefore, it is important to know which factors affect the space heating costs. This study aims to introduce the novel Rank Correlation Bayesian Network model and its application in analyzing the effects of dwelling characteristics on the space heating costs. The results show that the constructed Rank Correlation Bayesian Network model performed better than the Bayesian networks models estimated by Bayesian search, PC and Greedy Thick Thinning algorithms, which are kinds of structure learning algorithms having different kinds of estimation mechanisms to build Bayesian networks. The constructed Rank Correlation Bayesian Network model shows that the space heating costs of the dwellings are mostly affected by the heating systems used. Coal stoves, air conditioners and electric stoves appear to be the costliest heating systems. The second most important factor appears to be the existence of external wall insulation. The lack of external wall insulation almost doubles the space heating costs. The third most important factor is the building age. Dwellings on the ground floors and the first floors appear to pay the highest space heating costs. Therefore, dwellings on these floors need to be more effectively insulated. As the size of the dwelling increases the heating cost increases too. Another result is that facing directions and floor levels of the dwellings have the least effects on their space heating.

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

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

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

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

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

IEEE Access ◽  
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

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

Corrosion threat assessment of crude oil flow lines using Bayesian network model

2015 ◽  
Vol 50 (3) ◽  
pp. 236-247 ◽  
Author(s):  
G. Koch ◽  
F. Ayello ◽  
V. Khare ◽  
N. Sridhar ◽  
A. Moosavi
Keyword(s):  
Bayesian Network ◽  
Crude Oil ◽  
Network Model ◽  
Threat Assessment ◽  
Bayesian Network Model ◽  
Flow Lines ◽  
Oil Flow
Sign in / Sign up

Export Citation Format

Share Document