Amir Ghasemkhani
Amir Ghasemkhani
Assistant Professor of Computer Science and Engineering, California State University San Bernardino
Verified email at - Homepage
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Cited by
Optimal design of a wide area measurement system for improvement of power network monitoring using a dynamic multiobjective shortest path algorithm
A Ghasemkhani, H Monsef, A Rahimi-Kian, A Anvari-Moghaddam
IEEE Systems Journal 11 (4), 2303-2314, 2015
Adaptive Neural Network Based Intelligent Secondary Control for Microgrids
M Jafari, V Sarfi, A Ghasemkhani, H Livani, L Yang, H Xu, R Koosha
Power and Energy Conference (TPEC), IEEE Texas, 2018
Reinforcement Learning based Pricing for Demand Response
A Ghasemkhani, L Yang
Communications Workshops (ICC Workshops), 2018 IEEE International Conference on, 2018
An efficient multi-objective approach for designing of communication interfaces in smart grids
A Ghasemkhani, A Anvari-Moghaddam, JM Guerrero, B Bak-Jensen
2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2016
Multi-objective dispatch of distributed generations in a grid-connected micro-grid considering demand response actions
M Parvizimosaed, A Anvari-Moghaddam, A Ghasemkhani, A Rahimi-Kian
IET Digital Library, 2013
Learning-based Demand Response for Privacy-Preserving Users
A Ghasemkhani, L Yang, J Zhang
IEEE Transactions on Industrial Informatics, 2019
Biologically inspired adaptive intelligent secondary control for MGs under cyber imperfections
M Jafari, A Ghasemkhani, V Sarfi, H Livani, L Yang, H Xu
IET Cyber-Physical Systems: Theory & Applications 4 (4), 341-352, 2019
Decentralized Dynamic State Estimation with Missing and Delayed PMU Measurements
A Ghasemkhani, V Sarfi, L Yang, H Livani
2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 1-5, 2018
Adaptive Intelligent Secondary Control of Microgrids Using a Biologically-Inspired Reinforcement Learning
M Jafari, V Sarfi, A Ghasemkhani, H Livani, L Yang, H Xu
2019 IEEE Power & Energy Society General Meeting, 1-5, 2019
Multi-Attribute Distributed Generation Planning in a Micro-Grid Considering Uncertainty Conditions
A Ghasemkhani, M Setareh, A Anvari-Moghaddam, M Parvizi-Mosaed, ...
Proceedings of the 21st Iranian Conference on Electrical Engineering (icee), 1-6, 2013
A Regularized Tensor Completion Approach for PMU Data Recovery
A Ghasemkhani, I Niazazari, Y Liu, H Livani, VA Centeno, L Yang
IEEE Transactions on Smart Grid, 2020
Event Cause Analysis in Distribution Networks using Synchro Waveform Measurements
I Niazazari, H Livani, A Ghasemkhani, Y Liu, L Yang
arXiv preprint arXiv:2008.11582, 2020
Deep Neural Network based Wide-Area Event Classification in Power Systems
I Niazazari, A Ghasemkhani, Y Liu, S Biswas, H Livani, L Yang, ...
arXiv preprint arXiv:2008.10151, 2020
DeepGrid: Robust Deep Reinforcement Learning-based Contingency Management
A Ghasemkhani, A Darvishi, I Niazazar, A Darvishi, H Livani, L Yang
2020 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2020
Using Novel Machine Learning Algorithms to Improve the Spatiotemporal Coverage of Satellite Aerosol Optical Depth
J Huang, A Ghasemkhani, SM Loria Salazar, F Yan, L Yang, E Smirni, ...
AGUFM 2019, A13K-2978, 2019
Decentralized Dynamic State Estimation with Bimodal Gaussian Mixture Measurement Noise
V Sarfi, A Ghasemkhani, I Niazazari, L Yang, H Livani
2019 North American Power Symposium (NAPS), 1-5, 2019
Data Mining-Based Smart Energy Management System for Micro-grids
M Parvizi-Mosaed, F Farmani, A Ghasemkhani, A Anvari-Moghaddam, ...
Proceedings of the 28th International Power System Conference (psc), 1-8, 2013
A Decision Maker for Energy Management in Residential Micro-grids
F Farmani, M Parvizi-Mosaed, H Monsef, A Rahimi-Kian, A Ghasemkhani, ...
Proceedings of the 28th International Power System Conference (psc), 1-7, 2013
Smart Energy Management in a Micro-Grid Considering Demand Response Program
M Parvizi-Mosaed, A Anvari-Moghaddam, A Ghasemkhani, M Setareh, ...
Proceedings of the 27th International Power System Conference (psc), 1-8, 2012
Seasonal Self-evolving Neural Networks Based Short-term Wind Farm Generation Forecast
Y Liu, A Ghasemkhani, L Yang, J Zhao, J Zhang, V Vittal
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