Kim, Minhee, Ou, Elisa, Loh, Po-Ling, Allen, Todd, Agasie, Robert, and Liu, Kaibo. RNN-Based online anomaly detection in nuclear reactors for highly imbalanced datasets with uncertainty. Retrieved from https://par.nsf.gov/biblio/10289013. Nuclear Engineering and Design 364.C Web. doi:10.1016/j.nucengdes.2020.110699.

Kim, Minhee, Ou, Elisa, Loh, Po-Ling, Allen, Todd, Agasie, Robert, & Liu, Kaibo. RNN-Based online anomaly detection in nuclear reactors for highly imbalanced datasets with uncertainty. Nuclear Engineering and Design, 364 (C). Retrieved from https://par.nsf.gov/biblio/10289013. https://doi.org/10.1016/j.nucengdes.2020.110699

Kim, Minhee, Ou, Elisa, Loh, Po-Ling, Allen, Todd, Agasie, Robert, and Liu, Kaibo. "RNN-Based online anomaly detection in nuclear reactors for highly imbalanced datasets with uncertainty". Nuclear Engineering and Design 364 (C). Country unknown/Code not available. https://doi.org/10.1016/j.nucengdes.2020.110699. https://par.nsf.gov/biblio/10289013.

@article{osti_10289013,
place = {Country unknown/Code not available}, title = {RNN-Based online anomaly detection in nuclear reactors for highly imbalanced datasets with uncertainty}, url = {https://par.nsf.gov/biblio/10289013}, DOI = {10.1016/j.nucengdes.2020.110699}, abstractNote = {}, journal = {Nuclear Engineering and Design}, volume = {364}, number = {C}, author = {Kim, Minhee and Ou, Elisa and Loh, Po-Ling and Allen, Todd and Agasie, Robert and Liu, Kaibo}, editor = {null} }