李津, 史加荣, 张琰妮, 云斯宁. 基于最大信息系数的短期太阳辐射协同估计[J]. 太阳能学报, 2023, 44(9): 286-294. DOI: 10.19912/j.0254-0096.tynxb.2022-0693
引用本文: 李津, 史加荣, 张琰妮, 云斯宁. 基于最大信息系数的短期太阳辐射协同估计[J]. 太阳能学报, 2023, 44(9): 286-294. DOI: 10.19912/j.0254-0096.tynxb.2022-0693
Li Jin, Shi Jiarong, Zhang Yanni, Yun Sining. SHORT-TERM SOLAR RADIATION SYNERGY ESTIMATION BASED ON MAXIMUM INFORMATION COEFFICIENT[J]. Acta Energiae Solaris Sinica, 2023, 44(9): 286-294. DOI: 10.19912/j.0254-0096.tynxb.2022-0693
Citation: Li Jin, Shi Jiarong, Zhang Yanni, Yun Sining. SHORT-TERM SOLAR RADIATION SYNERGY ESTIMATION BASED ON MAXIMUM INFORMATION COEFFICIENT[J]. Acta Energiae Solaris Sinica, 2023, 44(9): 286-294. DOI: 10.19912/j.0254-0096.tynxb.2022-0693

基于最大信息系数的短期太阳辐射协同估计

SHORT-TERM SOLAR RADIATION SYNERGY ESTIMATION BASED ON MAXIMUM INFORMATION COEFFICIENT

  • 摘要: 提出一种短期太阳辐射估计的协同方法,即利用邻近站点数据来估计目标站点的太阳辐射。先利用最大信息系数对所有站点的相关数据进行特征选择。然后将特征选择后的数据作为输入,采用不同的机器学习模型进行估计。最后在实际数据上将协同估计的误差与仅采用目标站点的估计误差进行比较。实验结果表明协同估计对所有目标站点都有更高的精度和更低的误差。

     

    Abstract: To make precise and reliable estimation of solar radiation,this paper proposes a short-term solar radiation synergy estimation method,which implements adjacent station data to estimate solar radiation at target station. First,the maximum information coefficient is used to perform feature selection on relevant data from all stations. Then the data after feature selection are utilized as input for estimation using different machine learning models. The errors of the synergistic estimation are finally compared to the error taking only the target station data on real data. Experimental results indicate that the performance of the synergy estimation has a more precision and low error for all target stations,compared without synergy estimation.

     

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