Sparse KELM Online Prediction Model Based on Forgetting Factor

In the process of online prediction of nonstationary time series by kernel extreme learning machine (KELM), two problems appear that the order of kernel matrix is increasing and the system dynamic characteristics are difficult to be determined. A sparse KELM state prediction model based on forgettin...

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Veröffentlicht in:	2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) S. 1 - 6
Hauptverfasser:	Dai, Jinling, Xu, Aiqiang, Liu, Xing, Li, Ruifeng
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 20.11.2020
Schlagworte:	Dictionaries Extreme learning machines forgetting factor Kernel Kernel extreme learning machine kernel recursive least-squares algorithm online sequential learning Prediction algorithms Predictive models sparsity state prediction Time series analysis Windows
Online-Zugang:	Volltext
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