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基于LSTM-LGB模型的光伏电站辐照强度预测

王冉旭,何山,董广凯,董宁,邱瑞东

Journal of Anhui University(Natural Sciences)（2021）

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Abstract
为提高光伏电站辐照强度的预测精度,提出一种基于长短时记忆网络(long short term memory network,简称LSTM)和轻梯度提升机(light gradient boosting machine,简称LightGBM)的组合模型.以LightGBM模型的预测结果作为LSTM模型的一个特征输入,然后采用误差倒数法对以上两种模型的数据进行加权组合,得到组合模型的预测值.算例分析结果表明:与其他3种模型比较,该文组合模型的预测精度最高.
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