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References

1 
Power Exchange Korea, Sep 2014, A Study on Midterm Load Forecasting Technique based on Expert System and its Application, Korea Power ExchangeGoogle Search
2 
S. Jo, R. Park, K. Song, 2019, Jeju island’s special day load forecasting algorithm using dong-nae weather forecasting, Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, Vol. 33, No. 6, pp. 1-8Google Search
3 
of Trade Ministry, Dec 2020, The 9th basic Plan for Long-term Electricity Supply and Demand, Industry and EngergyGoogle Search
4 
Amanpreet Kaur, Lukas Nonnenmacher, Carlos F.M. Coimbra, 2016, Net load forecasting for high renewable energy penetration grids, Energy, Vol. 114, pp. 1073-1084DOI
5 
G.-H. Lee, G. Kwak, U. Chae, J.-D. KO, J.-Y. Lee, Dec 2020, Through load prediction and solar power generation prediction ESS operation plan(Guide-line) study, Journal of Digital Convergence, Vol. 18, No. 12, pp. 267-278DOI
6 
Seungmin Jung, 2019, An analysis about domestic irradiation statistic for plan on electricity demand and supply, The Journal of Next-generation Convergence Technology Association, Vol. 3, No. 3, pp. 125-131Google Search
7 
Si-Yeon Kim, Hyun-Woo Jung, Jeong-Do Park, Seung- Mook Baek, Woo-Seon Kim, Kyung-Hee Chon, Kyung-Bin Song, Jan 2014, Weekly Maximum Electric Load Forecasting for 104 Weeks by Seasonal ARIMA Model, Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, Vol. 28, No. 1, pp. 50-56DOI
8 
Desouky El, AA, MM Elkateb, 2000, Hybrid adaptive techniques for electric-load forecast using ANN and ARIMA, IEE Proceedings-Generation, Transmission and Distribution, Vol. 147, No. 4, pp. 213-217DOI
9 
K.Y Lee, Y.T. Cha, J.H. Park, 1992, Short-term load forecasting using an artificial neural network, IEEE Transactions on Power Systems, Vol. 7, No. 1, pp. 124-132DOI
10 
W. Kong, Z. Y. Dong, Y. Jia, D. J. Hill, Y. Xu, Y. Zhang, Jan 2019, Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network, in IEEE Transactions on Smart Grid, Vol. 10, No. 1, pp. 841-851DOI
11 
Bottou, L., 2010, Large-Scale Machine Learning with Stochastic Gradient Descent, Proceedings of COMPSTAT 2010, pp. 177-186DOI
12 
Diederik P. Kingma, Jimmy Ba, 2015, Adam: A Method for Stochastic Optimization, Proceedings of 3rd International Conference on Learning RepresentationsDOI
13 
S.M. Baek, 2019, Mid-term load pattern forecasting with recurrent artificial neural network, IEEE Access, Vol. 7, pp. 172830-172838DOI
14 
Ko Sangjun, Yun Hoyeong, Shin Dongmyung, 2018, Electronic Demand Data Prediction using Bidirectional Long Short Term Memory Networks, Journal of Software Assessment and Valuation, Vol. 14, No. 1, pp. 33-40Google Search
15 
Dohyun Kim, 2019, Short-term load forecasting based on LSTM and CNN, dissertation Konkuk UniversityGoogle Search
16 
Jeong-Do Park, Kyung-Bin Song., 2013, Short-Term Load Forecast for Summer Special Light-Load Period, The transactions of The Korean Institute of Electrical Engineers, Vol. 62, No. 4, pp. 482-488DOI
17 
Sung-Ill Kong, Young-Sik Baek, Kyung-Bin Song, Ji-Ho Park., 2004, The Daily Peak Load Forecasting in Summer with the Sensitivity of Temperature, The transactions of The Korean Institute of Electrical Engineers, Vol. 53a, No. 6, pp. 358-363Google Search