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- W2150538779 abstract "In this paper, a new multistage fuzzy neural network model is proposed to overcome the dimensionality problem of single-stage fuzzy neural networks. The model arranges single-stage reasoning stages in a multistage manner, where the consequence of one stage can be passed to the next stage as a fact. The network structure in each individual stage is developed based on Lin and Lee's (1991) fuzzy neural network model in which Mamdani's fuzzy reasoning is adopted. Given the stipulated input-output data pairs, an appropriate fuzzy rule set can be created through a hybrid learning process. Simulation Results show that the new model uses less resources than its single-stage counterpart to achieve favourable performance. Some interesting results have also been found in convergence and robustness." @default.
- W2150538779 created "2016-06-24" @default.
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- W2150538779 date "2002-11-27" @default.
- W2150538779 modified "2023-09-23" @default.
- W2150538779 title "A Mamdani type multistage fuzzy neural network model" @default.
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- W2150538779 doi "https://doi.org/10.1109/fuzzy.1998.686298" @default.
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