KIEE
The Transactions of
the Korean Institute of Electrical Engineers
KIEE
Contact
Open Access
Monthly
ISSN : 1975-8359 (Print)
ISSN : 2287-4364 (Online)
http://www.tkiee.org/kiee
Mobile QR Code
The Transactions of the Korean Institute of Electrical Engineers
ISO Journal Title
Trans. Korean. Inst. Elect. Eng.
Main Menu
Main Menu
최근호
Current Issue
저널소개
About Journal
논문집
Journal Archive
편집위원회
Editorial Board
윤리강령
Ethics Code
논문투고안내
Instructions to Authors
연락처
Contact Info
논문투고·심사
Submission & Review
Journal Search
Home
Archive
2021-11
(Vol.70 No.11)
10.5370/KIEE.2021.70.11.1625
Journal XML
XML
PDF
INFO
REF
References
1
Hye Jung Park, 2009, Quantile regression using asymmetric Laplace distribution, Journal of the Korean Data & Information Science Society. 2009, Vol. 20, No. 6, pp. 1093-1101
2
Byung-Hoon Ahn, Hoe-Ryeon Choi, Hong-chul Lee, 2015/12, Regional Long-term/Mid-term Load Forecasting using SARIMA in South Korea, The Korea Academia-Industrial cooperation Society, pp. 8576-8584
3
M. Baek, D.H. Lee, 2017, Spatial and Temporal Day-Ahead Total Daily Solar Irradiation Forecasting: Ensemble Forecasting Based on the Empirical Biasing
4
Yukseltan Ergun, Yucekaya Ahmat, Humeyra Bilge Ayse, 2020.09., Hourly electricity demand forecasting using Fourier analysis with feedback
5
Jin-Tae Kim, Seung-Yong Lee, Ji-Young Kim, 2020.9., Design of ESS Power Energy Capacity for Mitigation of Long-term Intermittent Wind Power Fluctuation, THE TRANSACTION OF THE KOREAN INSTITUTE OF ELECTRICAL ENGINEERS P 69P(3), pp. 175-180
6
Junho Song, Seungwook Yoon, Kanggu Park, Euiseok Hwang, 2017.11., Hybrid Day-ahead Prediction of Power Consumption based on Linear Prediction and Gaussian Process with Atypical Residual of Meteorological Information, The Korean Institute of Electrical Engineers, pp. 33-35
7
Gyoung-Do Kim, Yong-Hyuk Kim, 2017, A Survey on Oil Spill and Weather Forecast Using Machine Learning Based on Neural Networks and Statistical Methods, Journal of the Korea Convergence Society, Vol. 8, No. 10, pp. 1-8
8
R. Andrade José, Filipe Jorge, Reis Marisa, J. Bessa Ricardo, 2017/10, Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model
9
Nam BongWoo, Song KyungBin, Kim KyuHo, Cha JunMin, 2008, The Spatial Electric Load Forecasting Algorithm using the Multiple Regression Analysis Method, Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, Vol. 22, No. 2, pp. 63-70
10
P. P. K. Chan, W. C. Chen, W. W. Y. Ng, D. S.Yeung., 2011, Multiple classifier system for short term load forecast of Microgrid, 2011 International Conference on Machine Learning and Cybernetics(ICMLC), Vol. 3
11
H. M. Hwang, S. H. Lee, J. B. Park, Y. G. Park, S. Y. Son, 2015, Load Forecasting using Hierarchical Clustering Method for Building, The Transactions of the Korean Institute of Electrical Engineers, Vol. 64, No. 1, pp. 41-47
12
K. B. Song, 2014, Development of Short-Term Load Forecasting Algorithm Using Hourly Temperature, The Transactions of the Korean Institute of Electrical Engineers, Vol. 63, No. 4, pp. 451-454
13
Jinwoong Park, Jihoon Moon, Yongsung Kim, Eenjun Hwang, 2016/04, Electric Power Consumption Forecasting Method using Data Clustering
14
Liu Bidong, Nowotarski Jakub, Hong Tao, 2015/06, Probabilistic Load Forecasting via Quantile Regression Averaging on Sister Forecasts, IEEE Transcacsions on Smart Grid, pp. 730-737
15
Ben Taieb Souhaib, Huser Raphaei, G. Genton Marc, 2016/03, Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression, IEEE Transcacsions on Smart Grid, pp. 2448-2455
16
Xie Jingrui, Hong Tao, 2016/08, Temperature Scenario Generation for Probabilistic Load Forecasting, IEEE Transcacsions on Smart Grid, pp. 1680-1687
17
Wenjia Yang, Chongqing Kang, Qing Xia, Runsheng Liu, Taonan Tang, Peng Wang, 2016/08, Short Term Probabilistic Load Forecasting Baded on Statistics of Probability Distribution of Forecasting Errors, IEEE Transcacsions on Smart Grid, pp. 1680-1687
18
Yang Yandong, Li Shufang, Li Wenqi, Qu Meijun, 2018/03, Power Load Probability Density Forecasting Gaussian Process Quantile Regression, Applied Energy, pp. 499-509