A new approach to self-organizing fuzzy polynomial neural networks guided by genetic optimization

DOI10.1016/J.PHYSLETA.2005.06.100zbMath1345.92015OpenAlexW1997422071MaRDI QIDQ936939

Witold Pedrycz, Sung-Kwun Oh

Publication date: 20 August 2008

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physleta.2005.06.100

zbMATH Keywords

genetic optimizationmulti-layer perceptronfuzzy polynomial neuroncomputational intelligence (CI)fuzzy polynomial neural networks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59) Neural networks for/in biological studies, artificial life and related topics (92B20)

Uses Software

• Genocop

Cites Work

• Unnamed Item
• Ten years of genetic fuzzy systems: Current framework and new trends.
• Predicting a chaotic time series using a fuzzy neural network
• The design of self-organizing polynomial neural networks
• Automatic structure and parameter training methods for modeling of mechanical systems by recurrent neural networks.
• Fuzzy Polynomial Neuron-Based Self-Organizing Neural Networks
• Oscillation and Chaos in Physiological Control Systems

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