Adaptive linear and normalized combination of radial basis function networks for function approximation and regression

DOI10.1155/2014/913897zbMath1411.68128OpenAlexW1999206868WikidataQ59070696 ScholiaQ59070696MaRDI QIDQ1719381

Shanshan Yang, Yunfeng Wu, Xin Luo, Fang Zheng, Sin Chun Ng, Suxian Cai

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/913897

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Interpolation in approximation theory (41A05)

Uses Software

• UCI-ml
• fda (R)
• AdaBoost.MH
• bootstrap
• PRMLT

Cites Work

• Bagging predictors
• Knee joint vibration signal analysis with matching pursuit decomposition and dynamic weighted classifier fusion
• Functional data analysis
• A decision-theoretic generalization of on-line learning and an application to boosting
• Ensembling neural networks: Many could be better than all
• Multilayer feedforward networks are universal approximators
• Radial Basis Functions
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