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  • 學位論文

基於粒子群最佳化卷積神經網路進行短期負載預測

Short-Term Load Forecasting Using Particle Swarm Optimization-based Convolutional Neural Network

指導教授 : 洪穎怡
本文將於2027/07/25開放下載。若您希望在開放下載時收到通知,可將文章加入收藏

參考文獻


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[2] S. J. Huang and K. R. Shih, “Short-term load forecasting via ARMA model identification including non-gaussian process considerations,” IEEE Trans. Power Syst., vol. 18, no. 2, pp. 673–679, 2003.
[3] P. J. García Nieto, F. Sánchez Lasheras, E. García-Gonzalo, and F. J. de Cos Juez, “PM10 concentration forecasting in the metropolitan area of Oviedo (Northern Spain) using models based on SVM, MLP, VARMA and ARIMA: A case study,” Sci. Total Environ., vol. 621, pp. 753–761, 2018.
[4] C. M. Huang, C. J. Huang, and M. L. Wang, “A particle swarm optimization to identifying the ARMAX model for short-term load forecasting,” IEEE Trans. Power Syst., vol. 20, no. 2, pp. 1126–1133, 2005.
[5] J. W. Taylor, “Short-term load forecasting with exponentially weighted methods,” IEEE Trans. Power Syst., vol. 27, no. 1, pp. 458–464, 2012.

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