Zhao, Jin, Li, Fangxing, Mukherjee, Srijib, and Sticht, Christopher. Deep Reinforcement Learning-Based Model-Free On-Line Dynamic Multi-Microgrid Formation to Enhance Resilience. Retrieved from https://par.nsf.gov/biblio/10350162. IEEE Transactions on Smart Grid 13.4 Web. doi:10.1109/TSG.2022.3160387.

Zhao, Jin, Li, Fangxing, Mukherjee, Srijib, & Sticht, Christopher. Deep Reinforcement Learning-Based Model-Free On-Line Dynamic Multi-Microgrid Formation to Enhance Resilience. IEEE Transactions on Smart Grid, 13 (4). Retrieved from https://par.nsf.gov/biblio/10350162. https://doi.org/10.1109/TSG.2022.3160387

Zhao, Jin, Li, Fangxing, Mukherjee, Srijib, and Sticht, Christopher. "Deep Reinforcement Learning-Based Model-Free On-Line Dynamic Multi-Microgrid Formation to Enhance Resilience". IEEE Transactions on Smart Grid 13 (4). Country unknown/Code not available. https://doi.org/10.1109/TSG.2022.3160387. https://par.nsf.gov/biblio/10350162.

@article{osti_10350162,
place = {Country unknown/Code not available}, title = {Deep Reinforcement Learning-Based Model-Free On-Line Dynamic Multi-Microgrid Formation to Enhance Resilience}, url = {https://par.nsf.gov/biblio/10350162}, DOI = {10.1109/TSG.2022.3160387}, abstractNote = {}, journal = {IEEE Transactions on Smart Grid}, volume = {13}, number = {4}, author = {Zhao, Jin and Li, Fangxing and Mukherjee, Srijib and Sticht, Christopher}, }