Abstract
The automatic construction of fuzzy system with a large number of input variables involves many difficulties such as large time complexity and getting stuck in a shallow and local minimum. As models to overcome them, the SIRMs (Single Input Rule Modules) and DIRMs (Double Input Rule Modules) models have been proposed. However, they are not always effective. In this paper, we propose a model that consists of two phases: the first is a linear transformation of input to intermediate variables and the second is SIRMs model. It is shown that the proposed model has the same ability as the conventional model and does not need too much parameters. Further, it can be applied to classification problems with many variables easily.
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