Mahdi Khodayar
Mahdi Khodayar
Department of Computer Science - University of Tulsa
Verified email at utulsa.edu - Homepage
Title
Cited by
Cited by
Year
Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting
M Khodayar, O Kaynak, ME Khodayar
IEEE Transactions on Industrial Informatics 13 (6), 2770-2779, 2017
1422017
Spatio-temporal graph deep neural network for short-term wind speed forecasting
M Khodayar, J Wang
IEEE Transactions on Sustainable Energy 10 (2), 670-681, 2018
882018
Interval deep generative neural network for wind speed forecasting
M Khodayar, J Wang, M Manthouri
IEEE Transactions on Smart Grid 10 (4), 3974-3989, 2018
542018
Deep learning-based time-varying parameter identification for system-wide load modeling
M Cui, M Khodayar, C Chen, X Wang, Y Zhang, ME Khodayar
IEEE Transactions on Smart Grid 10 (6), 6102-6114, 2019
322019
Convolutional graph autoencoder: A generative deep neural network for probabilistic spatio-temporal solar irradiance forecasting
M Khodayar, S Mohammadi, ME Khodayar, J Wang, G Liu
IEEE Transactions on Sustainable Energy 11 (2), 571-583, 2019
292019
Robust deep neural network for wind speed prediction
M Khodayar, M Teshnehlab
2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), 1-5, 2015
242015
Energy disaggregation via deep temporal dictionary learning
M Khodayar, J Wang, Z Wang
IEEE transactions on neural networks and learning systems 31 (5), 1696-1709, 2019
172019
Probabilistic Time-Varying Parameter Identification for Load Modeling: A Deep Generative Approach
M Khodayar, J Wang
IEEE Transactions on Industrial Informatics, 2020
32020
Deep Generative Graph Distribution Learning for Synthetic Power Grids
M Khodayar, J Wang, Z Wang
https://arxiv.org/abs/1901.09674, 2019
32019
Deep Generative Graph Distribution Learning for Synthetic Power Grids
M Khodayar, J Wang, Z Wang
3*
Deep learning for pattern recognition of photovoltaic energy generation
M Khodayar, M Khodayar, SMJ Jalali
The Electricity Journal 34 (1), 1-6, 2021
22021
Spatiotemporal Behind-the-Meter Load and PV Power Forecasting via Deep Graph Dictionary Learning
M Khodayar, G Liu, J Wang, O Kaynak, M Khodayar
IEEE Transactions on Neural Networks and Learning Systems, 1-15, 2020
12020
Deep learning in power systems research: A review
M Khodayar, G Liu, J Wang, ME Khodayar
CSEE Journal of Power and Energy Systems, 2020
12020
Convolutional graph auto-encoder: A deep generative neural architecture for probabilistic spatio-temporal solar irradiance forecasting
M Khodayar, S Mohammadi, M Khodayar, J Wang, G Liu
arXiv preprint arXiv:1809.03538, 2018
12018
Morphological Reconfiguration Monitoring for Homogeneous Self-Reconfigurable Robots
M Macktoobian, AKN Tehrani, M Khodayar
12017
Towards Novel Deep Neuroevolution Models: Chaotic Levy Grasshopper Optimization for Short-term Wind Speed Forecasting
SMJ Jalali, S Ahmadian, M Khodayar, A Khosravi, V Ghasemi, ...
Engineering with Computers, 2021
2021
Maximum Relevance Minimum Redundancy Dropout with Informative Kernel Determinantal Point Process
M Saffari, M Khodayar, MS Ebrahimi Saadabadi, AF Sequeira, ...
Sensors 21 (5), 2021
2021
Learning Deep Architectures for Power Systems Operation and Analysis
M Khodayar
2020
Towards novel deep neuroevolution models: chaotic levy grasshopper optimization for short-term wind speed forecasting
SMJ Jalali, S Ahmadian, M Khodayar, A Khosravi, V Ghasemi
The system can't perform the operation now. Try again later.
Articles 1–19