Prediction indicators of unit 5 in KDD CUP.

<div><p>The accurate prediction of wind power is imperative for maintaining grid stability. In order to address the limitations of traditional neural network algorithms, the Informer model is employed for wind power prediction, delivering higher accuracy. However, due to insufficient exp...

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Bibliographic Details
Main Author:	Wenjuan Zhou (115285) (author)
Other Authors:	Feng Huang (62988) (author), Bing Wei (2588902) (author), Liang Li (46069) (author), Shixi Dai (22138931) (author), Xin Xie (311744) (author), Youyuan Peng (20862463) (author), Hong You (251402) (author)
Published:	2025
Subjects:	Biotechnology Astronomical and Space Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified reduce computation time maintaining grid stability experimental results demonstrate connected neural network computational efficiency deteriorate complex working conditions characterizes equipment performance blade deflection angle hidden coupling model delivering higher accuracy wind turbine operation dynamic synergistic coefficient higher prediction accuracy enhance prediction accuracy traditional informer model informer model based wind turbine data screen key multi power prediction experiments wind power prediction prediction accuracy informer model wind power wind speed prediction framework accurate prediction maintenance data informer ). dynamic correlations power output xlink "> study proposes source features new design lasso algorithm insufficient exploration health matrix health assessment assessment yields
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Prediction indicators of unit 5 in KDD CUP.

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