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Complex systems modeling via fuzzy logic   总被引:20,自引:0,他引:20  
This paper presents a fuzzy logic approach to complex systems modeling that is based on fuzzy discretization technique. As compared with other modeling methods (both statistical and fuzzy), the proposed approach has the advantages of simplicity, flexibility, and high accuracy. Further, it is easy to use and may be handled by an automatic procedure. Numerical examples are provided to illustrate the performance of the proposed approach.  相似文献
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This paper develops a new approach to building Sugeno-type models. The essential idea is to separate the premise identification from the consequence identification, while these are mutually related in the previous methods. A fuzzy discretization technique is suggested to determine the premise of the model, and an orthogonal estimator is provided to identify the consequence of the model. The orthogonal estimator can provide information about the model structure, or which terms to include in the model, and final parameter estimates in a very simple and efficient manner. The well-known gas furnace data of Box and Jenkins is used to illustrate the proposed modeling approach and to compare its performance with other statistical and fuzzy modeling approaches. It shows that the performance of the new approach compares favorably with these existing techniques  相似文献
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