Genetic programming for model selection of TSK-fuzzy systems

DOI10.1016/S0020-0255(01)00139-6zbMath0996.68155OpenAlexW2069262565MaRDI QIDQ1602474

Frank Hoffmann, Oliver Nelles

Publication date: 23 June 2002

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

Full work available at URL: https://doi.org/10.1016/s0020-0255(01)00139-6

zbMATH Keywords

genetic programmingneuro-fuzzy systemLOLIMOT

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Method for higher order polynomial Sugeno fuzzy inference systems ⋮ Prototype based granular neuro-fuzzy system for regression task ⋮ Ten years of genetic fuzzy systems: Current framework and new trends. ⋮ Incremental local linear fuzzy classifier in Fisher space ⋮ A genetic fuzzy agent using ontology model for meeting scheduling system. ⋮ Adaptive T-S fuzzy controller using reinforcement learning based on Lyapunov stability

Uses Software

• LOLIMOT
• ANFIS

Cites Work

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• Structure identification of fuzzy model
• Identifying fuzzy models utilizing genetic programming
• Identification of nonlinear system structure and parameters using regime decomposition
• Fuzzy identification of systems and its applications to modeling and control
• Genetic Fuzzy Systems