[HTML][HTML] Influence of resampling techniques on Bayesian network performance in predicting increased algal activity
Early warning of increased algal activity is important to mitigate potential impacts on aquatic
life and human health. While many methods have been developed to predict increased algal …
life and human health. While many methods have been developed to predict increased algal …
[HTML][HTML] Parallel structural learning of Bayesian networks: Iterative divide and conquer algorithm based on structural fusion
Abstract Learning Bayesian Networks (BNs) from high-dimensional data is a complex and
time-consuming task. Although the literature includes approaches based on horizontal …
time-consuming task. Although the literature includes approaches based on horizontal …
Predictive complex event processing based on evolving Bayesian networks
Y Wang, H Gao, G Chen - Pattern Recognition Letters, 2018 - Elsevier
Abstract In the Big Data era, large volumes of data are continuously and rapidly generated
from sensor networks, social network, the Internet, etc. Predicting from online event stream is …
from sensor networks, social network, the Internet, etc. Predicting from online event stream is …
An efficient skeleton learning approach-based hybrid algorithm for identifying Bayesian network structure
N Wang, H Liu, L Zhang, Y Cai, Q Shi - Engineering Applications of …, 2024 - Elsevier
Bayesian network (BN) structure learning is the basis of BN applications and plays a pivotal
role in many machine learning tasks. Whereas remarkable progress in structure learning …
role in many machine learning tasks. Whereas remarkable progress in structure learning …
Efficient and accurate structural fusion of Bayesian networks
Bayesian Network (BN) fusion provides a precise theoretical framework for aggregating the
graphical structure of a set of BNs into a consensus network. The fusion process depends on …
graphical structure of a set of BNs into a consensus network. The fusion process depends on …
The comprehensive safety assessment method for complex construction crane accidents based on scenario analysis–A case study of crane accidents
Crane accidents pose a significant safety hazard in the infrastructure construction process,
making a scientifically reliable safety assessment crucial. Addressing the limitations of …
making a scientifically reliable safety assessment crucial. Addressing the limitations of …
A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks
Abstract Learning Bayesian Networks (BNs) from high-dimensional data is a complex and
time-consuming task. Although there are approaches based on horizontal (instances) or …
time-consuming task. Although there are approaches based on horizontal (instances) or …
Distributed fusion-based algorithms for learning high-dimensional Bayesian Networks: Testing ring and star topologies
Abstract Learning Bayesian Networks (BNs) from high-dimensional data is a complex and
time-consuming task. Although there are approaches based on horizontal (instances) or …
time-consuming task. Although there are approaches based on horizontal (instances) or …
[PDF][PDF] 基于V-结构& 对数似然函数定向与禁忌爬山的贝叶斯网络结构算法
刘浩然， 王念太， 王毅， 张力悦， 苏昭玉， 刘文， 赵旭丹 - 电子与信息学报, 2021 - jeit.ac.cn
基于V-结构&对数似然函数定向与禁忌爬山的贝叶斯网络结构算法Bayesian Network Structure
Algorithm Ba Page 1 基于V-结构&对数似然函数定向与禁忌爬山的贝叶斯网络结构算法 刘浩然 …
Algorithm Ba Page 1 基于V-结构&对数似然函数定向与禁忌爬山的贝叶斯网络结构算法 刘浩然 …
[HTML][HTML] Improving Bayesian network local structure learning via data-driven symmetry correction methods
J Zhao, SS Ho - International Journal of Approximate Reasoning, 2019 - Elsevier
Learning the structure of a Bayesian network (BN) from data is NP-hard. To efficiently handle
high-dimensional datasets, many BN local structure learning algorithms are proposed …
high-dimensional datasets, many BN local structure learning algorithms are proposed …