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Bayesian network for predicting mandibular third molar extraction difficulty [PDF]
BMC Oral HealthBackground This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output ...
Tian Meng +3 more
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IEEE Access, 2022 To address the problem of low efficiency of the existing hill-climbing algorithm in Bayesian network structure learning, this paper proposes a Bayesian network structure learning algorithm based on probabilistic incremental analysis and constraints.
Haoran Liu +7 more
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Using consensus bayesian network to model the reactive oxygen species regulatory pathway. [PDF]
PLoS ONE, 2013 Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data ...
Liangdong Hu, Limin Wang
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Survey of Research on Non-homogeneous Gene Regulatory Network Models [PDF]
Jisuanji kexue yu tansuo, 2023 In the field of bioinformatics, the construction of gene regulatory networks is crucial. In recent years, non-homogeneous dynamic Bayesian networks have become a common modeling tool for learning gene regulatory networks from gene expression time-series ...
ZHANG Qianqian, HU Chunling, ZHANG Jiayao, LI Dawei, SHAO Mingyi
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Frontiers in Energy Research, 2022 Knowledge-driven and data-driven methods are the two representative categories of intelligent technologies used in fault diagnosis in nuclear power plants.
Ben Qi +3 more
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A Random Traffic Assignment Model for Networks Based on Discrete Dynamic Bayesian Algorithms
Discrete Dynamics in Nature and Society, 2022 In this paper, a stochastic traffic assignment model for networks is proposed for the study of discrete dynamic Bayesian algorithms. In this paper, we study a feasible method and theoretical system for implementing traffic engineering in networks based ...
Wei Zhou
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Smart Home IoT Network Risk Assessment Using Bayesian Networks
Entropy, 2022 A risk assessment model for a smart home Internet of Things (IoT) network is implemented using a Bayesian network. The directed acyclic graph of the Bayesian network is constructed from an attack graph that details the paths through which different ...
Miguel Flores +3 more
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Students' learning style detection using tree augmented naive Bayes [PDF]
Royal Society Open Science, 2018 Students are characterized according to their own distinct learning styles. Discovering students' learning style is significant in the educational system in order to provide adaptivity.
Ling Xiao Li, Siti Soraya Abdul Rahman
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Fault diagnosis of mine drainage system based on fuzzy Bayesian network
Gong-kuang zidonghua, 2022 The mine drainage system is developing towards automation and intelligence. The system's structure and function are becoming more and more complex, and the abnormal function and failure of a single component may cause the failure of the whole system. The
SHI Xiaojuan, YAO Bing, GU Huabei
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Integrating knowledge graph, complex network and Bayesian network for data-driven risk assessment
Chemical Engineering Transactions, 2022 Bayesian network is an effective method for quantitative risk assessment, but most existing studies are either heavily data-dependent or excessively expert-dependent.
Yiping Bai, Yuxuan Xing, Jiansong Wu
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