Takip et
Mahdi Khodayar
Mahdi Khodayar
Department of Computer Science - University of Tulsa
utulsa.edu üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
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
3422018
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
3092017
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
1582018
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
1392019
Deep learning in power systems research: A review
M Khodayar, G Liu, J Wang, ME Khodayar
CSEE Journal of Power and Energy Systems 7 (2), 209-220, 2020
1262020
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
872019
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
692019
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
532021
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
462015
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
442020
Deep learning for pattern recognition of photovoltaic energy generation
M Khodayar, M Khodayar, SMJ Jalali
The Electricity Journal 34 (1), 1-6, 2021
392021
Probabilistic Time-Varying Parameter Identification for Load Modeling: A Deep Generative Approach
M Khodayar, J Wang
IEEE Transactions on Industrial Informatics, 2020
362020
An advanced short-term wind power forecasting framework based on the optimized deep neural network models
SMJ Jalali, S Ahmadian, M Khodayar, A Khosravi, M Shafie-khah, ...
International Journal of Electrical Power & Energy Systems 141, 108143, 2022
342022
A New Ensemble Reinforcement Learning Strategy for Solar Irradiance Forecasting using Deep Optimized Convolutional Neural Network Models
SMJ Jalali, M Khodayar, S Ahmadian, M Shafie-khah, A Khosravi, ...
International Conference on Smart Energy Systems and Technologies (SEST), 1-6, 2021
202021
Stochastic Expansion Planning of Battery Energy Storage for the Interconnected Distribution and Data Networks  
AH Alobaidi, M Khodayar, A Vafamehr, H Gangammanavar, M Khodayar
International Journal of Electrical Power and Energy Systems, 2021
152021
Maximum Relevance Minimum Redundancy Dropout with Informative Kernel Determinantal Point Process
M Saffari, M Khodayar, MS Ebrahimi Saadabadi, AF Sequeira, ...
Sensors 21 (5), 2021
152021
Deep Convolutional Graph Rough Variational Auto-Encoder for Short-Term Photovoltaic Power Forecasting
M Saffari, M Khodayar, SMJ Jalali, M Shafie-khah, JPS Catalão
International Conference on Smart Energy Systems and Technologies (SEST), 1-6, 2021
152021
Deep Generative Graph Distribution Learning for Synthetic Power Grids
M Khodayar, J Wang, Z Wang
https://arxiv.org/abs/1901.09674, 2019
132019
Deep Generative Graph Distribution Learning for Synthetic Power Grids
M Khodayar, J Wang, Z Wang
13*
Solar irradiance forecasting using a novel hybrid deep ensemble reinforcement learning algorithm
SMJ Jalali, S Ahmadian, B Nakisa, M Khodayar, A Khosravi, S Nahavandi, ...
Sustainable Energy, Grids and Networks 32, 100903, 2022
122022
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