Results 51 to 60 of about 5,037,515 (156)

HyPE: Online Hybrid Pseudo-Bayesian Estimation Method for S-ALOHA-Based Tactical FANETs

IEEE Access
Significant challenges are involved in tactical flying ad-hoc network (FANET) missions because network environments are very dynamic. In addition, energy-efficient network operation is important in tactical FANETs owing to the limited capacity of the on ...
Jimin Jeon, Junseung Lee, Taewook Kim, Jaeha Ahn, Youngbin Yu, Min Lee, Heejung Yu, Howon Lee   +7 more
doaj   +1 more source

Bayesian network structure diagram.

, 2021
Bayesian network structure diagram.
Leyi Cheng (11273333), Shengxue Zhu (11273336), Yuming Jiang (645859), Yichuan Peng (5860055)   +3 more
core   +1 more source

Combining link and content-based information in a Bayesian inference model for entity search

, 2012
An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework.
Koumenides, Christos, Salvadores, Manuel, Omitola, Temitope, Shadbolt, Nigel   +3 more
core   +1 more source

Investigation of Bayesian network for reliability analysis and fault diagnosis of complex systems with real case applications

Advances in Mechanical Engineering, 2017
Reliability is critical for complex engineering systems. Traditionally, reliability analysis and fault diagnosis of complex engineering systems is based on reliability block diagram and fault tree.
Shen Chen, Zhen Qi, Dehuai Chen, Liangfu Guo, Weiwen Peng   +4 more
doaj   +1 more source

Urban Flood Mapping Using SAR Intensity and Interferometric Coherence via Bayesian Network Fusion

Remote Sensing, 2019
Synthetic Aperture Radar (SAR) observations are widely used in emergency response for flood mapping and monitoring. However, the current operational services are mainly focused on flood in rural areas and flooded urban areas are less considered.
Yu Li, Sandro Martinis, Marc Wieland, Stefan Schlaffer, Ryo Natsuaki   +4 more
doaj   +1 more source

Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

IEEE Access
Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties.
Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li   +6 more
doaj   +1 more source

Learning a bayesian network from ordinal data [PDF]

Bayesian networks are graphical models that represent the joint distributionof a set of variables using directed acyclic graphs. When the dependence structure is unknown (or partially known) the network can be learnt from data.
Flaminia Musella
core  

Integrating Bayesian network and generalized raking for population synthesis in Greater Jakarta

Regional Studies, Regional Science, 2019
Constructing agent data with detailed information on their sociodemographics is substantially important for agent-based modelling. However, to collect data about the whole population is not efficient, since it requires an expensive and time-consuming ...
Anugrah Ilahi, Kay W. Axhausen
doaj   +1 more source

Bayesian MAP model selection of chain event graphs [PDF]

, 2009
The class of chain event graph models is a generalisation of the class of discrete Bayesian networks, retaining most of the structural advantages of the Bayesian network for model interrogation, propagation and learning, while more naturally encoding ...
Freeman, Guy, Smith, J. Q.
core  

Causality, Propensity and Bayesian Networks [PDF]

, 2002
The notion of a Bayesian propensity network is introduced, and the relations between such networks and causal networks is investigated. It is argued that causal networks cannot be identified with Bayesian propensity networks, but that causal networks can
Gillies, D, Gillies, DA
core