• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
D. K. Ranaweera, G. G. Karady, R. G. Farmer, August 1997, Economic Impact Analysis of Load Forecasting, IEEE Trans. on Power Systems, Vol. 12, No. 3, pp. 1388-1392DOI
2 
C. H. Kim, 2013, Estimating Short-Term Load Forecasting in Korea Using Multiple exponential Smoothing, KERIGoogle Search
3 
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 Illuminating and Electrical Installation Engineers, Vol. 28, No. 1, pp. 50-56DOI
4 
X. Dong, L. Qian, L. Huang, 2017, Short-Term Load Forecasting In Smart Grid : A Combined CNN and K-Means Clustering Approach, IEEE Smart Computing and Big Data (BigComp), Vol. , No. , pp. 119-125DOI
5 
C. Tian, J. Ma, C. Zhang, P. Zhan, December 2018, A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network, Energies, 11, 3493DOI
6 
K. Y. Lee, Y. T. Cha, J. H. Park, February 1992, Short-Term Load Forecasting Using an Artificial Neural Network, IEEE Trans. on Power Systems, vol. 7, Vol. 7, No. 1, pp. 124-132DOI
7 
C. C. Hsu, C. Y. Chen, 2003, Regional Load Forecasting in Taiwan-Applications of Artificial Neural Networks, Energy Conversion and Management, Vol. 44, pp. 1941-1949DOI
8 
G. Sulligoi, A. Vincenzutti, R. Menis, December 2016, All-Electric Ship Design: From Electrical Propulsion to Integrated Electrical and Electronic Power Systems, IEEE Trans. on Transportation Electrification, Vol. 2, No. 4, pp. 507-521DOI
9 
H. K. Ku, H. R. Seo, J. M. Kim, August 2015, Lithium-ion Battery Energy Storage System for Power Quality Improvement in Electrical Propulsion Ships, The Trans. of the Korean Institute of Power Electronics, Vol. 20, No. 4, pp. 351-355DOI
10 
G. Tsamopoulos, N. Giannitsas, F. D. Kanellos, 2014, Load Estimation for War-Ships Based on Pattern Recognition Methods, Journal of Computations & Modeling, Vol. 4, No. 1, pp. 207-222Google Search
11 
J. Xiao, T. Zhang, X. Wang, 2005, Ship Power Load Prediction Based on RST and RBF Neural Networks, International Symposium on Neural Networks (ISNN), pp. 648-653DOI
12 
Y. LeCun, L. Bottou, Y. Bengio, P. Haffner, Nov 1998, Gradient- Based Learning Applied to Document Recognition, Proceedings of the IEEE, Vol. 86, pp. 2278-2324DOI
13 
S. Hochreiter, J. Schmidhuber, November 1997, Long Short-Term Memory, Neural Computation, Vol. 9, No. 8, pp. 1735-1780DOI
14 
Y. Bengio, P. Simard, P. Frasconi, March 1994, Learning Long- Term Dependencies with Gradient Descent is Difficult, IEEE Trans. on Neural Networks, Vol. 5, No. 2, pp. 157-166DOI
15 
M. Schuster, K. K. Paliwal, November 1997, Bidirectional Recurrent Neural Networks, IEEE Trans. on Signal Processing, Vol. 45, No. 11, pp. 2673-2681DOI
16 
K. He, X. Zhang, S. Ren, 2016, Deep residual learning for image recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770-778Google Search