Wind Power Prediction of Kernel Extreme Learning Machine Based on Differential Evolution Algorithm and Cross Validation Algorithm

As fossil fuel is being depleted, the percentage of wind power capacity in total electricity generation is increasing. In order to improve the absorption capacity of wind power, wind power prediction has been introduced. Aiming at the disadvantage of low prediction accuracy and unstable model of tra...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2020-01, Vol.8, p.1-1
Hauptverfasser:	Li, Ning, He, Fuxing, Ma, Wentao, Wang, Ruotong, Zhang, Xiaoping
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification algorithms Differential evolutionary algorithm Error functions Evolutionary algorithms Evolutionary computation Fossil fuels Genetic algorithms k fold cross validation Kernel Kernel extreme learning machine Kernels Machine learning Model accuracy Optimization Prediction algorithms Regularization Sociology Statistics Training Wind power Wind power generation wind power prediction
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!