Results 11 to 20 of about 520,634 (314)
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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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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Energy financial risk early warning model based on Bayesian network
Energy Reports, 2023 Oil is a global, non-renewable energy source, which plays a pivotal role in the development of the global economy and the strategic reserve system. With the expansion of crude oil futures trading scale, crude oil is no longer a pure energy commodity, but
Lin Wei, Hanyue Yu, Bin Li
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Research on Human Factors Reliability of Electric Power Enterprises Based on HFCRA Model [PDF]
SHS Web of Conferences, 2023 Based on Bayesian network, this paper establishes a human factor analysis tool-Human Factor Classification and Reliability Analysis (HFCRA) model, and analyzes the key factors of human error in power enterprises by combining the human events and data of ...
Liu Junfeng +3 more
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Loop amplitudes from precision networks
SciPost Physics Core, 2023 Evaluating loop amplitudes is a time-consuming part of LHC event generation. For di-photon production with jets we show that simple, Bayesian networks can learn such amplitudes and model their uncertainties reliably.
Simon Badger, Anja Butter, Michel Luchmann, Sebastian Pitz, Tilman Plehn
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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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CAAI Transactions on Intelligence Technology, 2023 The battlefield situation changes rapidly because underwater targets' are concealment and the sea environment is uncertain. So, a great number of situation information greatly increase, which need to be dealt with in the course of scouting underwater ...
Yongqin Sun +3 more
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Evaluation of a Bayesian inference network for ligand-based virtual screening [PDF]
, 2009 Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to
A Abdo +45 more
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Improving Bayesian statistics understanding in the age of Big Data with the bayesvl R package [PDF]
, 2020 The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics.
Ho, Manh-Toan +5 more
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Journal of Industrial Engineering and Management, 2016 Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain.
Faycal Mimouni, Abdellah Abouabdellah
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