A review of federated meta-learning and its application in cyberspace security

F Liu, M Li, X Liu, T Xue, J Ren, C Zhang - Electronics, 2023 - mdpi.com
In recent years, significant progress has been made in the application of federated learning
(FL) in various aspects of cyberspace security, such as intrusion detection, privacy …

A combined deep learning and physical modelling method for estimating air pollutants' source location and emission profile in street canyons

Y Zhou, Y An, W Huang, C Chen, R You - Building and Environment, 2022 - Elsevier
Roadside air pollution monitoring stations have become frequently available for street
canyons. To efficiently estimate source location and emission profile in street canyons, this …

Deep learning-based source term estimation of hydrogen leakages from a hydrogen fueled gas turbine

A Li, Z Lang, C Ni, H Tian, B Wang, C Cao, W Du… - International Journal of …, 2024 - Elsevier
Hydrogen fueled gas turbine is an efficient and environmentally friendly energy conversion
equipment. However, it is prone to gas leakages from corrosion-prone components and pipe …

Hybrid Deep Learning and Sensitivity Operator-Based Algorithm for Identification of Localized Emission Sources

A Penenko, M Emelyanov, E Rusin, E Tsybenova… - Mathematics, 2023 - mdpi.com
Hybrid approaches combining machine learning with traditional inverse problem solution
methods represent a promising direction for the further development of inverse modeling …

A Novel Multi-Sensor Data-Driven Approach to Source Term Estimation of Hazardous Gas Leakages in the Chemical Industry

Z Lang, B Wang, Y Wang, C Cao, X Peng, W Du… - Processes, 2022 - mdpi.com
Source term estimation (STE) is crucial for understanding and addressing hazardous gas
leakages in the chemical industry. Most existing methods basically use an atmospheric …