Cover Image

A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Yuandi, Sicard, Brett, Gadsden, Stephen Andrew
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multivariate Physics-Informed Convolutional Autoencoder for Anomaly Detection in Power Distribution Systems with High Penetration of DERs
by: Zideh, Mehdi Jabbari, et al.
Published: (2024)

Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection
by: HaghighiFard, M. Saeid, et al.
Published: (2024)

SOLIS: Physics-Informed Learning of Interpretable Neural Surrogates for Nonlinear Systems
by: Mansur, Murat Furkan, et al.
Published: (2026)

Application of Zone Method based Physics-Informed Neural Networks in Reheating Furnaces
by: Dutta, Ujjal Kr, et al.
Published: (2023)

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN
by: Hossain, Muhammad Imran, et al.
Published: (2025)

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow with Continual Learning
by: Ezeakunne, Chidozie, et al.
Published: (2026)

Time and Frequency Domain-based Anomaly Detection in Smart Meter Data for Distribution Network Studies
by: Labura, Petar, et al.
Published: (2025)

Forecasting Day-Ahead Electricity Prices in the Integrated Single Electricity Market: Addressing Volatility with Comparative Machine Learning Methods
by: Harkin, Ben, et al.
Published: (2024)

Improving Variational Autoencoder using Random Fourier Transformation: An Aviation Safety Anomaly Detection Case-Study
by: Asanjan, Ata Akbari, et al.
Published: (2026)

Learning Contextual Runtime Monitors for Safe AI-Based Autonomy
by: Luque-Cerpa, Alejandro, et al.
Published: (2026)

Online Model-based Anomaly Detection in Multivariate Time Series: Taxonomy, Survey, Research Challenges and Future Directions
by: Correia, Lucas, et al.
Published: (2024)

A Systems Theoretic Approach to Online Machine Learning
by: Preez, Anli du, et al.
Published: (2024)

Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
by: Tesfazgi, Samuel, et al.
Published: (2025)

Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)

Preparing for Black Swans: The Antifragility Imperative for Machine Learning
by: Jin, Ming
Published: (2024)

Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
by: Modirshanechi, Alireza, et al.
Published: (2026)

MA-VAE: Multi-head Attention-based Variational Autoencoder Approach for Anomaly Detection in Multivariate Time-series Applied to Automotive Endurance Powertrain Testing
by: Correia, Lucas, et al.
Published: (2023)

Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges
by: van der Sar, Erica, et al.
Published: (2025)

Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies
by: Ahang, Maryam, et al.
Published: (2024)

On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence
by: Huang, Jian, et al.
Published: (2026)

Novelty Detection in Reinforcement Learning with World Models
by: Zollicoffer, Geigh, et al.
Published: (2023)

Integrating Reinforcement Learning and Model Predictive Control with Applications to Microgrids
by: da Silva, Caio Fabio Oliveira, et al.
Published: (2024)

Towards Machine Learning-based Model Predictive Control for HVAC Control in Multi-Context Buildings at Scale via Ensemble Learning
by: Deng, Yang, et al.
Published: (2025)

Physics-Informed Deep Learning and Partial Transfer Learning for Bearing Fault Diagnosis in the Presence of Highly Missing Data
by: Kavianpour, Mohammadreza, et al.
Published: (2024)

Reinforcement Learning-enabled Satellite Constellation Reconfiguration and Retasking for Mission-Critical Applications
by: Alami, Hassan El, et al.
Published: (2024)

Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics
by: Schneevogt, Malte, et al.
Published: (2024)

A Black-Box Physics-Informed Estimator based on Gaussian Process Regression for Robot Inverse Dynamics Identification
by: Giacomuzzos, Giulio, et al.
Published: (2023)

Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review
by: Nyangon, Joseph
Published: (2026)

Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
by: Rosemberg, Andrew, et al.
Published: (2025)

Adaptive Torque Control of Exoskeletons under Spasticity Conditions via Reinforcement Learning
by: Chavarrías, Andrés, et al.
Published: (2025)

A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System
by: Lin, Zong-Zhi, et al.
Published: (2022)

DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data
by: Chen, Hanyang, et al.
Published: (2024)

DIAL: Distribution-Informed Adaptive Learning of Multi-Task Constraints for Safety-Critical Systems
by: Yoo, Se-Wook, et al.
Published: (2025)

Success Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
by: Russo, Daniel
Published: (2026)

Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems
by: Bagheri, Maryam, et al.
Published: (2022)

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
by: Liu, Yushen, et al.
Published: (2026)

Meta-Reinforcement Learning for Building Energy Management System
by: Zhang, Huiliang, et al.
Published: (2022)

A Review on AI Algorithms for Energy Management in E-Mobility Services
by: Yan, Sen, et al.
Published: (2023)

Bregman Centroid Guided Cross-Entropy Method
by: Gu, Yuliang, et al.
Published: (2025)

Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)