Results 11 to 20 of about 6,628,841 (378)
A Variational Beam Model for Failure of Cellular and Truss‐Based Architected Materials
Advanced Engineering Materials, EarlyView., 2023 Herein, a versatile and efficient beam modeling framework is developed to predict the nonlinear response and failure of cellular, truss‐based, and woven architected materials. It enables the exploration of their design space and the optimization of their mechanical behavior in the nonlinear regime. A variational formulation of a beam model is presented
Konstantinos Karapiperis +3 more
wiley +1 more source
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
doaj +1 more source
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
doaj +1 more source
A Symbolic Approach to Explaining Bayesian Network Classifiers [PDF]
International Joint Conference on Artificial Intelligence, 2018 We propose an approach for explaining Bayesian network classifiers, which is based on compiling such classifiers into decision functions that have a tractable and symbolic form.
Andy Shih, Arthur Choi, Adnan Darwiche
semanticscholar +1 more source
Bayesian Networks in Reliability [PDF]
Reliability Engineering & System Safety, 2007 Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of statistical problems. We have also seen a growing interest for using BNs in the reliability analysis community. This article discusses the properties of the modeling framework that are of highest importance for reliability practitioners. Keywords:
Langseth, Helge, Jensen, Finn V.
openaire +7 more sources
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
doaj +1 more source
Bayesian Neural Networks [PDF]
, 2022 In recent times, neural networks have become a powerful tool for the analysis of complex and abstract data models. However, their introduction intrinsically increases our uncertainty about which features of the analysis are model-related and which are due to the neural network.
Charnock, Tom +2 more
openaire +2 more sources
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
doaj +1 more source
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
doaj +1 more source
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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