DỰ BÁO SẢN LƯỢNG ĐIỆN TỈNH BẠC LIÊU DÙNG MẠNG HỌC SÂU
Thông tin bài báo
Ngày nhận bài: 20/12/21                Ngày hoàn thiện: 16/02/22                Ngày đăng: 23/02/22Tóm tắt
Từ khóa
Toàn văn:
PDFTài liệu tham khảo
[1] Bac Lieu Power Co., Project of electricity development planning of Bac Lieu province in the period 2016-2025 with a view to 2035, Bac Lieu, 2015.
[2] A. Ghanbari, A. Naghavi, S. F. Ghaderi, and M. Sabaghian, "Artificial Neural Networks and regression approaches comparison for forecasting Iran's annual electricity load," in 2009 International Conference on Power Engineering, Energy and Electrical Drives, 18-20 March 2009, pp. 675-679, doi: 10.1109/POWERENG.2009.4915245.
[3] W. Mansour, M. Moenes, H. Mahmoud, and A. Ghareeb, "Long term load forecasting for the egyptian network using ann and regression models," presented at the 21st International Conference on Electricity Distribution, Frankfurt, 6-9 June 2011.
[4] V. B. Doan, "Electricity energy mid-term forecasting in Vietnam using neural networks," presented at the 35 years Anerversary Conference of Vietnam Academy of Science and Technology, Ha Noi, 10/2010, pp. 335-339.
[5] B. T. T. Phan and M. V. Luong, "Load forecasting by regression model based on fuzzy rules," Science & Technology Development, VNU-HCM City, vol. 17, no. K1-2014, pp. 30-36, 2014.
[6] Y. Li and D. Niu, "Application of Principal Component Regression Analysis in power load forecasting for medium and long term," in 2010 3rd Inter. Conf. on Advanced Computer Theory and Engineering (ICACTE), 20-22 Aug. 2010, vol. 3, pp. V3-201-V3-203, doi: 10.1109/ICACTE.2010.5579658.
[7] C. Hamzaçebi, "Forecasting of Turkey's net electricity energy consumption on sectoral bases," Energy Policy, vol. 35, no. 3, pp. 2009-2016, 2007, doi: https://doi.org/10.1016/j.enpol. 2006.03.014.
[8] V. Shrivastava and R. B. Misra, "A Novel Approach of Input Variable Selection for ANN Based Load Forecasting," in 2008 Joint Inter. Conf. on Power System Technology and IEEE Power India Conference, 12-15Oct.2008, pp. 1-5, doi: 10.1109/ICPST.2008.4745348.
[9] D. Ali, M. Yohanna, M. I. Puwu, and B. M. Garkida, "Long-term load forecast modelling using a fuzzy logic approach," Pacific Science Review A: Natural Science and Engineering, vol. 18, no. 2, pp. 123-127, July 01, 2016, doi: https://doi.org/10.1016/j.psra.2016.09.011.
[10] F. C. Torrini, R. C. Souza, F. L. Cyrino Oliveira, and J. F. Moreira Pessanha, "Long term electricity consumption forecast in Brazil: A fuzzy logic approach," Socio-Economic Planning Sciences, vol. 54, pp. 18-27, June 01, 2016, doi: https://doi.org/10.1016/j.seps.2015.12.002.
[11] K. M. El-Naggar and K. A. AL-Rumaih, "Electric Load Forecasting Using Genetic Based Algorithm, Optimal Filter Estimator and Least Error Squares Technique: Comparative Study," World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol. 1, pp. 953-957, 2007.
[12] A. Gupta and P. K. Sarangi, "Electrical load forecasting using genetic algorithm based back-propagation method," ARPN Journal of Engineering and Applied Sciences, vol. 7, no. 8, pp. 1017-1020, 2012.
[13] Y. Shi, H. Yang, Y. Ding, and N. Pang, "Research on Long Term Load Forecasting Based on Improved Genetic Neural Network," in 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 19-20 Dec. 2008, vol. 2, pp. 80-84, doi: 10.1109/PACIIA.2008.313.
[14] P.-F. Pai and W.-C. Hong, "Forecasting regional electricity load based on recurrent support vector machines with genetic algorithms," Electric Power Systems Research, vol. 74, no. 3, pp. 417-425, June 01, 2005, doi: https://doi.org/10.1016/j.epsr.2005.01.006.
[15] T.-N. Nguyen, T.-H. Tran and C.-N. Nguyen, "A Forecasting Model for Monitoring Water Quality in Aquaculture and Fisheries IoT Systems," in 2020 International Conference on Advanced Computing and Applications (ACOMP), 25-27 Nov. 2020, pp. 165-169, doi: 10.1109/ACOMP50827.2020.00033.
[16] T.-N. Nguyen, T.-H. Nguyen and C.-N Nguyen, "Deep Learning Approach for Forecasting Water Quality in IoT Systems," Inter. J. of Advanced Computer Science and Applications, vol. 11, no. 8, pp. 686-693, 2020.
[17] B. Lim and S. Zohren, "Time-series forecasting with deep learning: A survey," Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 379, no. 2194, 2020, doi: 10.1098/rsta.2020.0209.
[18] The Mathworks Inc., "Long Short-Term Memory Networks," in Documentations, ed, 2021.
[19] S. Hochreiter and J. Schmidhuber, "Long Short-Term Memory," Neural Computation, vol. 9, no. 8, pp. 1735-1780, 1997, doi: 10.1162/neco.1997.9.8.1735.
[20] BP, "Statistical Review of World Energy". [Online]. Available: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html. [Accessed Dec. 20, 2021].
[21] H. Ritchie and M. Roser, "Sweden: Energy Country Profile," OurWorldInData. [Online]. Available: https://ourworldindata.org/ energy/country/sweden. [Accessed Dec. 20, 2021].
[22] T. Vu, "EVN surprises with improved financial situation in 2020," Institute of Energy Economics and Financial Analysis (IEEFA), July 2021. [Online]. Available: https://ieefa.org/. [Accessed Dec. 20, 2021].DOI: https://doi.org/10.34238/tnu-jst.5362
Các bài báo tham chiếu
- Hiện tại không có bài báo tham chiếu