The new method of flatness pattern recognition based on GA-RBF-ARX and comparative research

DOI10.1007/s11071-015-2428-zzbMath1351.68246OpenAlexW1898768192MaRDI QIDQ335508

Xiu-Ling Zhang, Shuang Hao, Yong-Jin Lai, Long Cheng, Wu-Yang Gao

Publication date: 2 November 2016

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11071-015-2428-z

zbMATH Keywords

genetic algorithmflatness pattern recognitionHopfield NNRBF-ARX model

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (1)

Anti-disturbance control for HVs system subject to nonlinear actuator characteristics with extended state observer

Uses Software

• Matlab
• GSA

Cites Work

• Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression
• GSA: A gravitational search algorithm
• Identification and modeling of nonlinear dynamical systems using a novel self-organizing RBF-based approach
• Structured parameter optimization method for the radial basis function-based state-dependent autoregressive model

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