Abstract: Learning dynamical networks based on time series of nodal states is of significant interest in systems science, computer science, and control engineering. Despite recent progress in network ...
Abstract: Uncertainty in climate change poses challenges in obtaining accurate and reliable prediction models for future pavement performance. This study aimed to develop an advanced prediction model ...
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 ...
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 ...
Abstract: Hyperspectral images (HSIs) provide detailed spectral information, which are effective for change detection (CD). Prior knowledge has been proven to improve the robustness of models in HSI ...
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 ...
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 ...
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 ...
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 ...
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 ...
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