Results 1 to 10 of about 520,634 (314)
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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Semiparametric Bayesian networks
Information Sciences, 2022 We introduce semiparametric Bayesian networks that combine parametric and nonparametric conditional probability distributions. Their aim is to incorporate the advantages of both components: the bounded complexity of parametric models and the flexibility of nonparametric ones.
Atienza González, David +2 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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Bayesian Network Classifiers [PDF]
Machine Learning, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Friedman, Nir +2 more
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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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Spectral Bayesian network theory
Linear Algebra and its Applications, 2023 22 pages, 6 ...
Luke Duttweiler +2 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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Bayesian network–response regression [PDF]
Bioinformatics, 2017 Abstract Motivation There is increasing interest in learning how human brain networks vary as a function of a continuous trait, but flexible and efficient procedures to accomplish this goal are limited.
Wang, Lu +3 more
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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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