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- W2390499483 abstract "In this paper,a new approach,the multicriteria learning(MCL) algorithm based on a composite criterion including both fuzzy entropy and mean-squared error criterion,is proposed for training multi layer max-min neural networks.The new algorithm overcomes the limitations in mono-criterion learning,that is,the mean-squared error criterion will easily converging to a local minimum value and slow converging speed.Compared with the traditional fuzzy back-propagation(FBP) algorithm,it is found that the proposed MCL algorithm provides a faster learning speed and higher stability." @default.
- W2390499483 created "2016-06-24" @default.
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- W2390499483 date "2007-01-01" @default.
- W2390499483 modified "2023-09-23" @default.
- W2390499483 title "A multi-criteria learning method for multi-layer fuzzy neural networks" @default.
- W2390499483 hasPublicationYear "2007" @default.
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