Uncertainties in conditional probability tables of discrete Bayesian Belief Networks: A comprehensive review
J Rohmer - Engineering Applications of Artificial Intelligence, 2020 - Elsevier
Abstract Discrete Bayesian Belief Network (BBN) has become a popular method for the
analysis of complex systems in various domains of application. One of its pillar is the …
analysis of complex systems in various domains of application. One of its pillar is the …
[HTML][HTML] Network-based approaches for modeling disease regulation and progression
Molecular interaction networks lay the foundation for studying how biological functions are
controlled by the complex interplay of genes and proteins. Investigating perturbed processes …
controlled by the complex interplay of genes and proteins. Investigating perturbed processes …
Assessment of the organizational factors in incident management practices in healthcare: A tree augmented Naive Bayes model
S Albreiki, MCE Simsekler, A Qazi, A Bouabid - Plos one, 2024 - journals.plos.org
Despite the exponential transformation occurring in the healthcare industry, operational
failures pose significant challenges in the delivery of safe and efficient care. Incident …
failures pose significant challenges in the delivery of safe and efficient care. Incident …
Application of a Bayesian network modelling approach to predict the cascading effects of COVID-19 restrictions on the planting activities of smallholder farmers in …
CONTEXT There are rising concerns over the cascading effects induced by COVID-19
restrictions on the planting activities of smallholder farmers in low and middle-income …
restrictions on the planting activities of smallholder farmers in low and middle-income …
Estimating runway veer-off risk using a Bayesian network with flight data
DJ Barry - Transportation Research Part C: Emerging …, 2021 - Elsevier
Risk assessments in airline operations are mostly qualitative, despite abundant data from
programmes such as flight data monitoring (FDM) and flight operations quality assurance …
programmes such as flight data monitoring (FDM) and flight operations quality assurance …
What are the relevant sources and factors affecting event mean concentrations (EMCs) of nutrients and sediment in stormwater?
Urbanization increases runoff, sediment, and nutrient loadings downstream, causing
flooding, eutrophication, and harmful algal blooms. Stormwater control measures (SCMs) …
flooding, eutrophication, and harmful algal blooms. Stormwater control measures (SCMs) …
[HTML][HTML] Influence of resampling techniques on Bayesian network performance in predicting increased algal activity
Early warning of increased algal activity is important to mitigate potential impacts on aquatic
life and human health. While many methods have been developed to predict increased algal …
life and human health. While many methods have been developed to predict increased algal …
[HTML][HTML] Bayesian Networks for Prescreening in Depression: Algorithm Development and Validation
Background Identifying individuals with depressive symptomatology (DS) promptly and
effectively is of paramount importance for providing timely treatment. Machine learning …
effectively is of paramount importance for providing timely treatment. Machine learning …
[图书][B] Procedural content generation via machine learning: An Overview
This book surveys current and future approaches to generating video game content with
machine learning or Procedural Content Generation via Machine Learning (PCGML) …
machine learning or Procedural Content Generation via Machine Learning (PCGML) …
Dynamic failure analysis of ship energy systems using an adaptive machine learning formalism
Dynamic Failure Analysis of Ship Energy Systems Using an Adaptive Machine Learning
Formalism Page 1 Received: 31 October 2022 | Revised: 19 January 2023 | Accepted: 20 …
Formalism Page 1 Received: 31 October 2022 | Revised: 19 January 2023 | Accepted: 20 …