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K. H. Kim, R. J. Park, S. W. Jo, K. B. Song, 2017, 24-Hour Load Forecasting Algorithm Using Artificial Neural Network in Summer Weekdays, Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, Vol. 31, No. 12, pp. 113-119Google Search
C. H. Kim, 2013, Estimating Short-Term Load Forecasting in Korea Using Multiple exponential Smoothing, KERIGoogle Search
S. Y. Kim, H. W. Jung, J. D. Park, S. M. Baek, W. S. Kim, K. H. Chon, K. B. Song, 2014, Weekly Maximum Electric Load Forecasting for 104 Weeks by Seasonal ARIMA Model, Journal of the Korean Institute of Illminating and Electrical Installation Engineers, Vol. 28, No. 1, pp. 50-56DOI
C. N. Ko, C. M. Lee, Dec 2012, Short-term load forecasting using SVR (support vector regression)-based radial basis function neural network with dual extended Kalman filter, ELSEVIER Energy, Vol. 49, pp. 413-422DOI
H. Takeda, Y. Tamura, S. Sato, Apr 2016, Using the ensemble Kalman filter for electricity load forecasting and analysis, Energy, Vol. 104, pp. 184-198DOI
S. Li, L. Goel, W. Wang, Mar 2016, An ensemble approach for short-term load forecasting by extreme learning machine, ELSEVIER Applied Energy, Vol. 170, pp. 22-29DOI
Y. Feng, S. M. Ryan, Mar 2016, Day-ahead hourly electricity load modeling by functional regression, Applied Energy, Vol. 170, pp. 455-465DOI
V. N. Coelho, I. M. Coelho, B. N. Coelho, A. J. Reis, M. J. Enayatifar, F. G. Guimaraes, Feb 2016, A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment, Applied Energy, Vol. 169, pp. 567-584DOI
Y. Yang, J. Che, Y. Li, Y. Zhao, S. Zhu, Jul 2016, An incremental electric load forecasting model based on support vector regression, Energy, Vol. 113, pp. 796-808DOI
H. S. Tak, T. Y. Kim, H. G. Cho, H. J. Kim, Nov 2016, A New Prediction Model for Power Consumption with Local Weather Information, Journal of THE Korea Contents Association, Vol. 16, No. 11, pp. 488-498DOI
S. Ha, K. Song, H. Kim, 2005, Short-Term Load Forecasting Using Neural Networks and the Sensitivity of Temperatures in the Summer Season, The Transactions of KIEE, Vol. 54a, No. 6, pp. 259-266Google Search
J. Han, J. Baek, 2010, The Load Forecasting in Summer Considering Day Factor, The Transactions of KAIS, Vol. 11, No. 8, pp. 2793-2800DOI
Y. Park, B. Wang, 2004, Neuro-Fuzzy Model based Electrical Load Forecasting System, The Transactions of KIIS, Vol. 14, No. 5, pp. 553-538DOI
M. K. Kim, C. E. Hong, Jan 2016, The Artificial Neural Network based Electric Power Demand Forecast using a Season and Weather Informations, The Transactions of the Korean Institute of Electrical Engineers, Vol. 53, No. 1, pp. 71-78DOI
SungMahn Ahn, 2016, Deep Learning Architectures and Applications, Journal of Intelligence and Information Systems, Vol. 22, No. 2, pp. 127-142DOI
H. Jang, S. Cho, 2016, Automatic Tagging for Social Images using Convolution Neural Networks, Journal of KIISE, Vol. 43, No. 1, pp. 37-53DOI
S. M. Chi, May 2018, Architectures of Convolutional Neural Networks for the Prediction of Protein Secondary Structures, Journal of the Korea Institute of Information and Communication Engineering, Vol. 22, No. 5, pp. 728-733DOI
Y. Kim, Y. Hwang, T. Kang, K. Jung, May 2016, LSTM Language Model Based Korean Sentence Generation, The Journal of The Korean Institute of Communication Sciences, Vol. 41, No. 5, pp. 592-601DOI
K. B. Song, O. S. Kwon, J. D. Park, 2013, Optimal Coefficient Selection of Exponential Smoothing Model in Short Term Load Forecasting on Weekdays, The Transactions of the Korean Institute of Electrical Engineers, Vol. 63, pp. -DOI
B. S. Kwon, R. J .Park, K. B. Song, 2018, Analysis of Short-Term Load Forecasting Accuracy Based on Various Normalization Methods, Journal of the Korean Institute of IIIuminating and Electrical Installation Engineers, Vol. 32, No. 6Google Search