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- W2360726598 abstract "With the goal of improving the speed and accuracy of fuzzy modeling for nonlinear system,a fast and effective method based on data-mining is proposed.In the process of fuzzy structure identification,an improved subtractive clustering combined with fuzzy c-means clustering are introduced to speed up the modeling by solving the problem of initialization of FCM and reducing the calculation of clustering simultaneously.Then the consequence parameter identification is obtained by the recursive least-square algorithm with dynamic forgetting factor,which can low the dynamic error and improve the accuracy.The simulation results of Box-Jenkins gas furnace and Expander show the effectiveness of this approach." @default.
- W2360726598 created "2016-06-24" @default.
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- W2360726598 date "2011-01-01" @default.
- W2360726598 modified "2023-09-26" @default.
- W2360726598 title "A New Method for Fuzzy Modeling Based on Data-mining" @default.
- W2360726598 hasPublicationYear "2011" @default.
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