(1.School of Electrical & Information Engineering, Changsha University of Science & Technology, Changsha 410114, China; 2.College of Computer Science and Technology,Zhejiang University, Hangzhou 310058,China;3.Electric Power Research Institute,State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330006,China)
TM61
彭曙蓉,彭家宜,杨云皓,张 恒,李 彬,王冠南.基于时变深度前馈神经网络的风电功率概率密度预测[J].电力科学与技术学报英文版,2023,38(3):84-93. PENG Shurong, PENG Jiayi, YANG Yunhao, ZHANG Heng, LI Bin, WANG Guannan. Wind power probability density prediction based on time‑variant deep feed‑forward neural network[J]. Journal of Electric Power Science and Technology,2023,38(3):84-93.
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