Support vector fuzzy adaptive network in regression analysis
作者： Judong Shen , Yu-Ru Syau , E.S. Lee
DOI: 10.1016/J.CAMWA.2007.03.006
关键词:
摘要: Neural-fuzzy systems have been proved to be very useful and applied modeling many humanistic problems. But these also problems such as those of generalization, dimensionality, convergence. Support vector machines, which are based on statistical learning theory kernel transformation, powerful tools. However, they do not the ability represent aggregate vague ill-defined information. In this paper, two combined. The resulting support fuzzy adaptive network (SVFAN) overcomes some difficulties neural-fuzzy system. To illustrate proposed approach, a simple nonlinear function is estimated by first generating training testing data needed. results show that tool.
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