Acknowledgement
본 연구는 한국전력공사 전력연구원의 2017년 자체과제로 수행한 '상태추론 기반 배전설비 예지 기술 및 엔진 개발' 연구과제의 기술개발 결과임.
References
- Warren, Chris "Can Artificial Intelligence Transform the Power System?" KEPCO Journal on Electric Power and Energy v.5. no.2, 2019.
- Negnevitsky, Michael, Paras Mandai, Anurag K. Srivastava, "Machine learning applications for load, price and wind power prediction in power systems," 15th international conference on Intelligent System Applications to Power Systems, IEEE, 2009.
- Kelp, S. M., Sanjay V. Dudul. "Short-term Maharashtra state electrical power load prediction with special emphasis on seasonal changes using a novel focused time lagged recurrent neural network based on time delay neural network model," Expert System with Applications 38. 3, 2011.
- Hall, Mark A, Lloyd A. Smith, "Practical feature subset selection for machine learning," Proceeding of the 21st Australasian Computer Science Conference ACSC'98, 1998.
- Batista, Gustavo EAPA, Ronaldo C. Prati, Maria Carolina Monard. "A study of the behavior of several methods for balancing machine learning training data," ACM SIGKDD explorations newsletter 6.1, 2004.
- Hullemeier, Eyke. "Fuzzy methods in machine learning and data mining: Status and prospects," Fuzzy sets and Systems, 156 (3), 2005.
- De Myttenaere, Arnaud, Colden, B., Le Grand, B., Rossi F., "Mean absolute percentage error for regression models," Neurocomputing, 192. 2016.
- Voyant, C., Notton, G., Kalogirous, S., Nivet, M. L, Paoli C., Motte, F., Fouilloy, A., "Machine learning methods for solar radiation forecasting: A review," Renewable Energy, 105, 2017.
- Theocharides, Spyros., Makrides, G., Georghiou, G. E., Kyprianous, A., "Machine learning algorithms for photovoltaic system power output prediction," Proceeding of the 2018 IEEE International Energy Conference, 2018.
- De Myttenarare, Arnaud, Golden, B., Le Grand, B., Rossi, F, "Mean absolute percentage error for regression models," Neurocomputing, 192, 2016.