A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3070878
Abstract: In this article, we develop a hybrid physics-informed neural network (hybrid PINN) for partial differential equations (PDEs). We borrow the idea from the convolutional neural network (CNN) and finite volume methods. Unlike the physics-informed neural… read more here.
Keywords: neural network; physics; hybrid physics; informed neural ... See more keywords
A Hybrid Physics-Based Data-Driven Framework for Anomaly Detection in Industrial Control Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3131662
Abstract: A method referred to as PbNN is proposed to detect cyber-physical attacks through the identification of resulting anomalies in the process dynamics of the underlying ICS. Unlike existing anomaly detectors based on an abstract knowledge… read more here.
Keywords: hybrid physics; based data; physics; systems hybrid ... See more keywords