Hierarchical convolutional neural networks for event classification on PMU measurements M Pavlovski, M Alqudah, T Dokic, AA Hai, M Kezunovic, Z Obradovic IEEE Transactions on Instrumentation and Measurement 70, 1-13, 2021 | 35 | 2021 |
Transfer learning for event detection from PMU measurements with scarce labels AA Hai, T Dokic, M Pavlovski, T Mohamed, D Saranovic, M Alqudah, ... IEEE Access 9, 127420-127432, 2021 | 18 | 2021 |
Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units MK Alqudah, M Pavlovski, T Dokic, M Kezunovic, Y Hu, Z Obradovic IEEE Transactions on Power Systems, 2021 | 15 | 2021 |
Automated power system fault prediction and precursor discovery using multi-modal data M Alqudah, M Kezunovic, Z Obradovic IEEE Access 11, 7283-7296, 2022 | 7 | 2022 |
Prediction of solar radiation based on spatial and temporal embeddings for solar generation forecast M Alqudah, T Dokic, M Kezunovic, Z Obradovic Proceedings of the IEEE Hawaii International Conference on System Sciences …, 2020 | 7 | 2020 |
Enhancing Weather-Related Outage Prediction and Precursor Discovery Through Attention-Based Multi-Level Modeling M Alqudah, Z Obradovic IEEE Access, 2023 | 5 | 2023 |
Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART) M Kezunovic, T Djokic, R Baembitov, T Mohamed, Z Obradovic, AA Hai, ... Texas A & M Univ., College Station, TX (United States), 2022 | 1 | 2022 |
Learning From Multi-Modal Spatiotemporal Data: Machine Learning Approaches to Advance Resilience in Smart Grids MK Alqudah Temple University, 2023 | | 2023 |