Kernel general loss algorithm based on evolving participatory learning for online time series prediction

Author:

Han MinORCID,Xia HuijuanORCID,Ren WeijieORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference38 articles.

1. A novel rule-based evolving fuzzy system applied to the thermal modeling of power transformers;Alves;Appl. Soft Comput.,2021

2. An enhanced set-membership evolving participatory learning with kernel recursive least squares applied to thermal modeling of power transformers;Alves;Electr. Power Syst. Res.,2020

3. Evolving Takagi-Sugeno fuzzy systems from streaming data (eTS+);Angelov;Evolv. Intell. Syst.: Methodol. Appl.,2010

4. An approach to online identification of Takagi-Sugeno fuzzy models;Angelov;IEEE Trans. Syst. Man Cybern. B,2004

5. Simpl_eTS: A simplified method for learning evolving Takagi-Sugeno fuzzy models;Angelov,2005

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Random Fourier Features Kernel Recursive Generalized Loss for Online Time Series Prediction;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07

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