The Study of System Model Based on Fuzzy Inference and Neural Network

Ming Ming Gao; Liang Shan

doi:10.4028/www.scientific.net/AMM.197.547

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 197The Study of System Model Based on Fuzzy Inference...

The Study of System Model Based on Fuzzy Inference and Neural Network

Abstract:

For the characteristics of fuzziness, indeterminacy etc. in nonlinear systems, this paper, combining fuzzy inference system with neural network, Adaptive Neural Fuzzy Inference System model had been provided in the paper, ANFIS method is based on Sugeno fuzzy model and has a structure similar to neural network that tunes the parameters of the fuzzy inference system with back propagation algorithm and least - square method and can produce fuzzy rules automatically. This solutes extraction of fuzzy rules and learning of parameters of membership functions play an essential role in the design. This paper gives the simulation example of modeling a typical system with ANFIS method and good result is obtained.

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Periodical:

Applied Mechanics and Materials (Volume 197)

Pages:

547-552

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.197.547

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Online since:

September 2012

Authors:

Ming Ming Gao, Liang Shan

Keywords:

ANFIS, Membership Function, Modeling, Nonlinear System, Simulation

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References

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