Fuzzy slopes model of nonlinear systems with sparse data

In this paper, a fuzzy slopes model is introduced for the modeling of nonlinear systems with sparse data. The proposed method is the combination of the slopes and fuzzy models. The slopes model is used to estimate the missing output data of a nonlinear behavior; later, the fuzzy model is used to learn this behavior. The proposed method avoids the requirement to know all the data. The output of the slopes algorithm is guaranteed to be bounded. The experiments show the effectiveness of the proposed technique.