基于ROF的短期风速极端学习机集成预测
기우ROF적단기풍속겁단학습궤집성예측
  • 万方数据
    数字技术与应用 수자기술여응용
    DIGITAL TECHNOLOGY AND APPLICATION
    2014年 8期 97-97 ,共1页

    敖培%李贺%李怀芝%赵四方%冯志鹏

    오배%리하%리부지%조사방%풍지붕

    旋转森林%极端学习机短期风速预测 鏇轉森林%極耑學習機短期風速預測
    선전삼림%겁단학습궤단기풍속예측
    ROF%ELM%short-term wind speed prediction
    为了对风速进行准确的预测,本文提出一种基于ROF的ELM集成预测算法,即采用ROF算法产生差异性训练数据训练多个个体ELM,然后利用加权平均的方法集成各个体ELM的预测结果。实验表明,与个体预测模型相比,该算法有更高的预测精度。
    위료대풍속진행준학적예측,본문제출일충기우ROF적ELM집성예측산법,즉채용ROF산법산생차이성훈련수거훈련다개개체ELM,연후이용가권평균적방법집성각개체ELM적예측결과。실험표명,여개체예측모형상비,해산법유경고적예측정도。
    In order to predict wind speed accurately, an ELM ensemble algorithm based on ROF is proposed in this paper. Firstly, ROF algorithm is used to produce diversity data to train individual ELMs. Secondly, weighted averaging method is used to col ect the prediction results of individual ELMs. Verified by an example, this algorithm is better than individual prediction model.
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