Combining forecasts: a fuzzy approach

In this paper, we investigate the use of first order Takagi-Sugeno fuzzy systems (TS1) [19] to combine a set of individual forecasts; Such systems can be interpreted as local linear approximation models and have been used mainly as such in this study. The inference produced by these models can be, seen as a new kind of piecewise linear regression with softened transitions between the pieces. We crompare-TS1 with traditional linear combining models and we show the advantage of this nonlinear approach as well as the flexibility of our system.