Kamruzzaman, Md., Duan, Jiajun, Shi, Di, and Benidris, Mohammed. A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources. Retrieved from https://par.nsf.gov/biblio/10315640. IEEE Transactions on Power Systems 36.6 Web. doi:10.1109/TPWRS.2021.3078446.

Kamruzzaman, Md., Duan, Jiajun, Shi, Di, & Benidris, Mohammed. A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources. IEEE Transactions on Power Systems, 36 (6). Retrieved from https://par.nsf.gov/biblio/10315640. https://doi.org/10.1109/TPWRS.2021.3078446

Kamruzzaman, Md., Duan, Jiajun, Shi, Di, and Benidris, Mohammed. "A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources". IEEE Transactions on Power Systems 36 (6). Country unknown/Code not available. https://doi.org/10.1109/TPWRS.2021.3078446. https://par.nsf.gov/biblio/10315640.

@article{osti_10315640,
place = {Country unknown/Code not available}, title = {A Deep Reinforcement Learning-Based Multi-Agent Framework to Enhance Power System Resilience Using Shunt Resources}, url = {https://par.nsf.gov/biblio/10315640}, DOI = {10.1109/TPWRS.2021.3078446}, abstractNote = {}, journal = {IEEE Transactions on Power Systems}, volume = {36}, number = {6}, author = {Kamruzzaman, Md. and Duan, Jiajun and Shi, Di and Benidris, Mohammed}, }