Complex system fault diagnosis based on a fuzzy robust wavelet support vector classifier and an adaptive Gaussian particle swarm optimization

DOI10.1016/J.INS.2010.08.006zbMath1207.68254OpenAlexW2072273345MaRDI QIDQ621586

Qi Wu, Rob Law

Publication date: 28 January 2011

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2010.08.006

zbMATH Keywords

fault diagnosisparticle swarm optimizationGaussian mutationadaptive mutationwavelet kernel function

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (7)

Statistical modeling of gear vibration signals and its application to detecting and diagnosing gear faults ⋮ Fault detection and diagnosis of non-linear non-Gaussian dynamic processes using kernel dynamic independent component analysis ⋮ Modeling and monitoring for handling nonlinear dynamic processes ⋮ Fuzzy reasoning spiking neural P system for fault diagnosis ⋮ Multiple sequence alignment using the hidden Markov model trained by an improved quantum-behaved particle swarm optimization ⋮ Integrating support vector regression with particle swarm optimization for numerical modeling for algal blooms of freshwater ⋮ A short-term wind power forecasting method based on hybrid-kernel least-squares support vector machine

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