本发明公开的基于多级GateSATCN的光伏功率预测方法,属于电气工程领域.本发明在TCN的基础上引入注意力机制,得到数据加权处理后的特征提取结果,将处理后的特征向量展开成一维向量输入全连接层,预测光伏发电功率;多级门控正向优化网络根据校正结果和门控权重,对前一阶段的预测结果进行优化,并计算均方误差RMSE作为损失函数;...
1.基于多级Gate-SA-TCN的光伏功率预测方法,其特征在于,包括如下步骤: S1对历史光伏发电功率数据进行预处理,包括对异常数据的删除,对缺失数据的补充,最后进行归一化处理; S2通过输入层将预处理后的数据输入到多级Gate-SA-TCN进行大规模的网络训练,所述预处理后的数据包括:不同温度,光照,风速条件下的历史光伏发电功率...
Forecasting Gate-Front Water Levels Using a Coupled GRU–TCN–Transformer Model and Permutation Entropy Algorithm by Jiwei Zhao, Taotao He *, Luyao Wang and Yaowen Wang Water Conservancy College, North China University of Water Resources and Electric Power, Zhengzhou 450046, China * Author to wh...
Forecasting Gate-Front Water Levels Using a Coupled GRU–TCN–Transformer Model and Permutation Entropy Algorithm by Jiwei Zhao, Taotao He *, Luyao Wang and Yaowen Wang Water Conservancy College, North China University of Water Resources and Electric Power, Zhengzhou 450046, China * Author to wh...
「米汀Nagisa」Hacking to the Gate 2024.12.28 04:14 「米汀Nagisa」Que Sera Sera 2024.12.28 03:16 「米汀Nagisa」太陽系デスコ/太阳系disco 2024.12.28 03:22 「米汀Nagisa」あなたに出会わなければ~夏雪冬花~ 2024.12.30 05:57 「米汀Nagisa」in fact 2024.12.30 04:19 「米汀Nagisa」silly ...
本发明公开的基于多级GateSATCN的光伏功率预测方法,属于电气工程领域.本发明在TCN的基础上引入注意力机制,得到数据加权处理后的特征提取结果,将处理后的特征向量展开成一维向量输入全连接层,预测光伏发电功率;多级门控正向优化网络根据校正结果和门控权重,对前一阶段的预测结果进行优化,并计算均方误差RMSE作为损失函数;...
Automatic animal headgate with bottom hinged gatesJerry D WadePhillip H Geisler
Addressing the nonlinearity and non-stationarity characteristics of gate-front water level sequences, this paper introduces a gate-front water level forecasting method based on a GRU–TCN–Transformer coupled model and permutation entropy (PE) algorithm. Firstly, an analysis method combining Singular ...
Addressing the nonlinearity and non-stationarity characteristics of gate-front water level sequences, this paper introduces a gate-front water level forecasting method based on a GRU–TCN–Transformer coupled model and permutation entropy (PE) algorithm. Firstly, an analysis method combining Singular ...
Addressing the nonlinearity and non-stationarity characteristics of gate-front water level sequences, this paper introduces a gate-front water level forecasting method based on a GRU–TCN–Transformer coupled model and permutation entropy (PE) algorithm. Firstly, an analysis method combining Singular ...