IEEE

A Physics-Guided Bayesian Neural Network for Sensor Fault Detection in Wind Turbines

Abstract: Predictive maintenance is essential for ensuring the reliability and efficiency of wind energy systems. Traditional deep learning models for sensor fault detection rely solely on data-driven ...
IEEE

Fast Charging of Lithium-Ion Batteries Using Deep Bayesian Optimization With Recurrent Neural Network

Abstract: Fast charging has attracted increasing attention from the battery community for electrical vehicles (EVs) to alleviate range anxiety and reduce charging time for EVs. However, inappropriate ...
IEEE

Real-Time Bayesian Neural Networks for 6G Cooperative Positioning and Tracking

Abstract: In the evolving landscape of 5G new radio and related 6G evolution, achieving centimeter-level dynamic positioning is pivotal, especially in cooperative intelligent transportation system ...
IEEE

Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

Abstract: Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas ...
IEEE

Implementation of Bayesian Network Based on Ultra-High-Speed Superconductor Random Number Generators

Abstract: A Bayesian network (BN) is a graphical model that represents causal relationships between events. BNs have been widely used in applications such as forecasting, diagnosis, and classification ...
IEEE

Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information

Abstract: Landslides are major natural hazards that pose significant threats to life, property, and economic stability, particularly in vulnerable regions such as China. Among various approaches for ...
IEEE

Bayesian Spatio-Temporal Graph Convolutional Network for Railway Train Delay Prediction

Abstract: This study introduces a novel approach that integrates dynamic Bayesian network with attention based spatio-temporal graph convolutional network to forecast railway train delays, capturing ...
IEEE

Graph Embedding-Based Bayesian Network for Fault Isolation in Complex Equipment

Abstract: Fault isolation, or fault location, aims to identify anomalous components at the start of the maintenance process. However, fault isolation within complex equipment can be challenging due to ...