Regression Fuzzy Neural Network and Applications in Forecasting
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thanhnm@hcmute.edu.vnKeywords:
Recurrent Fuzzy Neural Network (RFNN), nonlinear systemsAbstract
The paper represented a Recurrent Fuzzy Neural Network (RFNN). Temporal relations are embedded in the network by adding feedback connections in the second layer of the fuzzy neural network (FNN). The RFNN expands the basic ability of the FNN to cope with temporal problems. The RFNN is applied in time series prediction, identification, and control of nonlinear systems.
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References
Nguyễn Hoàng Phương, Bùi Công Cường, Nguyễn Doãn Phước, Phan Xuân Minh, Chu Văn Hỷ, Hệ mờ và ứng dụng, Nhà xuất bản khoa học và kỹ thuật, 1998.
Ching-Hung Lee and Ching-Cheng Teng, Idetification and Control of Dynamic Systems Using Recurrent Fuzzy Neural Networks, IEEE Trans. Fuzzy Systems, Vol.8, pp. 349 – 366.
Chin-Teng Lin & C.S. Geogre Lee, Neural Fuzzy Systems, Prentice-Hall International, Inc.
Tom M. Mitchell, Machine Learning, McGraw-Hill, 1997.
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