BERT-Text CNN和BERT-LSTM预测效果较好;最后,基于上述基线模型的不足和公告文本的挖掘,提出XGB-BERT-LSTM模型即:使用准确率作为数据加权的计算基础,将基于BERT-LSTM的披露公告文本预测模型,与基于XGBoost的结构化数据基线预测模型应用集成方法,得出:改进的模型XGB-BERT-LSTM相较于本文的其他模型效果最好,预测准确度能够...
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None Environment Latest Container Image Output 883.5 kB Time # Log Message 17.7s1Over 0.99 probability: 730 17.7s2Less than 0.01 probability: 2594 21.6s3/opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2567: FutureWarning: --Exporter.preprocessors=["remove_papermill_header.RemovePapermill...
视频 日期筛选 27 生活不会一直绿灯 但红灯也会倒计时 生活不会一直绿灯 但红灯也会倒计时 33 唱完倒带 到时候倒车入库包过#吉他弹唱#倒带 唱完倒带 到时候倒车入库包过#吉他弹唱#倒带 14 回不去的何止是时间#回忆 回不去的何止是时间#回忆 22 你说 我那天看你的眼神这么温柔#爱上了一个人眼睛不说慌#射手...
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为了充分利用电网自身的海量历史数据进行光伏功率预测,提出一种宽度&深度(Wide&Deep)框架下融合极限梯度提升(XGBoost)算法和长短时记忆网络(LSTM)的Wide&Deep-XGB2LSTM超短期光伏功率预测模型.对历史数据进行特征提取,获得时间,辐照度,温度等原始特征,在此基础上进行特征重构,通过交叉组合和挖掘统计特征构造辐照度×辐照...
massive historical data of power grid for photovoltaic power prediction,XGBoost (eXtreme Gradient Boosting) algorithm and LSTM(Long Short-Term Memory network) are fused under Wide & Deep framework,and a ultra-short-term photovoltaic power prediction model based on Wide & Deep-XGB2LSTM ...
基于Wide&Deep-XGB2LSTM模型的超短期光伏功率预测
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