Additive dynamic Bayesian networks for enhanced feature learning in soft sensor modeling
Due to the advantages of indicating variable structure and efficient reasoning, Bayesian
Networks (BN) have been widely used in data-driven soft sensor applications. However …
Networks (BN) have been widely used in data-driven soft sensor applications. However …
Short-term load forecasting of regional integrated energy system based on spatio-temporal convolutional graph neural network
Z Su, G Zheng, M Hu, L Kong, G Wang - Electric Power Systems Research, 2024 - Elsevier
Accurate short-term load forecasting has significant reference value for the preliminary
planning and subsequent coordinated control of regional integrated energy systems …
planning and subsequent coordinated control of regional integrated energy systems …
Study on a new metaheuristic algorithm–Tribal intelligent evolution optimization and its application in optimal control of cooling plants
Y Yao, X Hong, L Xiong - Applied Energy, 2025 - Elsevier
This study proposes a new metaheuristic algorithm called Tribal Intelligent Evolution
Optimization (TIEO). This algorithm is inspired by the process of continuous division and …
Optimization (TIEO). This algorithm is inspired by the process of continuous division and …
[HTML][HTML] Spatial air quality prediction in urban areas via message passing
Air pollution in urban areas poses a significant and pressing challenge for modern society.
Unfortunately, the existing network of pollution detectors in many cities is limited in scope …
Unfortunately, the existing network of pollution detectors in many cities is limited in scope …
AICrit: A Design-Enhanced Anomaly Detector and Its Performance Assessment in a Water Treatment Plant
Critical Infrastructure Security Showdown 2021—Online (CISS2021-OL) represented the fifth
run of iTrust's international technology assessment exercise. During this event, researchers …
run of iTrust's international technology assessment exercise. During this event, researchers …
Deep learning and ensemble methods for anomaly detection in ICS security
MA Hossain, T Hasan, V Karovic jr… - International Journal of …, 2024 - Springer
This research addresses the escalating threats to industrial control systems by introducing a
novel approach that combines deep learning for feature selection with a robust ensemble …
novel approach that combines deep learning for feature selection with a robust ensemble …
Research on spatial-temporal synergistic sensor fault diagnosis method for top-blowing furnace
D Jiang, J Zhao - ISA transactions, 2024 - Elsevier
Top-blowing furnace systems, characterized by a large number of sensors and harsh
working environments, are prone to sensor failures due to factors like component aging and …
working environments, are prone to sensor failures due to factors like component aging and …
[HTML][HTML] Anomaly Detection and Analysis in Nuclear Power Plants
Industries are increasingly adopting digital systems to improve control and accessibility by
providing real-time monitoring and early alerts for potential issues. While digital …
providing real-time monitoring and early alerts for potential issues. While digital …
Explainable Intrusion Detection in Industrial Control Systems
R Eltomy, W Lalouani - 2024 IEEE 7th International …, 2024 - ieeexplore.ieee.org
In the realm of smart manufacturing, Industrial Control Systems (ICSs) play a critical role in
supervising essential operations across various manufacturing facilities. As ICSs become …
supervising essential operations across various manufacturing facilities. As ICSs become …
Networks in Social Networks
J Wu - Social Network Computing, 2024 - Springer
This chapter focuses on the tools and techniques of social network analysis, emphasizing
the study of network structures and relationships. Concepts such as centrality, clustering …
the study of network structures and relationships. Concepts such as centrality, clustering …