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A novel two‐stage interval prediction method based on minimal gated memory network for clustered wind power forecasting

机译：一种基于基于最小门控存储网络的新型两阶段间隔预测方法，用于集群风电预测

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Jianxun Lang; Xiaosheng Peng; Wenze Li; Tao Cai; Zhenhao Gan; Shanxun Duan; Chaoshun Li;
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1. A novel two-stage interval prediction method based on minimal gated memory network for clustered wind power forecasting [J] . Lang Jianxun, Peng Xiaosheng, Li Wenze, Wind Energy . 2021,第5期

机译：一种基于基于最小门控存储网络的新型两阶段间隔预测方法，用于集群风电预测
2. Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation [J] . Zhang Zhendong, Qin Hui, Liu Yongqi, Energy Conversion & Management . 2019,第SEPa期

机译：基于分位数回归最小门控记忆网络和核密度估计的风速预测
3. Deep Learning Method Based on Gated Recurrent Unit and Variational Mode Decomposition for Short-Term Wind Power Interval Prediction [J] . Wang Ruoheng, Li Chaoshun, Fu Wenlong, Neural Networks and Learning Systems, IEEE Transactions on . 2020,第10期

机译：基于门控复发单元的深度学习方法和短期风电间隔预测的变分模式分解
4. Aggregated wind power prediction methods based on distances between weather forecasting vectors [C] . International Conference on Clean Electrical Power . 2009

机译：基于天气预报向量距离的聚集风力预测方法
5. Short Term Wind Power Forecast Error Analysis Using Statistical Methods --- A Study of the Reduction of the Regional Aggregated Wind Power Forecast Error by Spatial Smoothing Effects in the Maritimes. [D] . Han, Yu. 2008

机译：使用统计方法的短期风电预测误差分析---通过海上空间平滑效应减少区域性总风电预测误差的研究。
6. TRSWA-BP Neural Network for Dynamic Wind Power Forecasting Based on Entropy Evaluation [O] . Shuangxin Wang, Xin Zhao, Meng Li, 2018

机译：基于熵评估的TRSWA-BP神经网络动态风力预测
7. Adequacy Assessment of a Wind-Integrated System Using Neural Network-based Interval Predictions of Wind Power Generation and Load [O] . Ak Ronay, Li Yan-Fu, Vitelli Valeria, 2013

机译：基于神经网络的风力发电和负荷区间预测的风综合系统充分性评估

A novel two‐stage interval prediction method based on minimal gated memory network for clustered wind power forecasting

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