A non-linear clustering method for fuzzy time series: Histogram damping partition under the optimized cluster paradox

- The clustering problem is an emergent issue in fuzzy time series.
- The existing clustering methods deal with the number of clusters or their size.
- Optimized cluster paradox refers to that trade-off between size and number.
- The histogram damping algorithm (HDP) is proposed to deal with this problem by estimating a proper cluster form with number and size characteristics.
- The proposed model is tested against the conventional methods and the case of random data is also presented. Results indicated superiority of the proposed method.