| Full text | |
| Author(s): |
Pinto, Nilmara J. B.
;
Wasques, Vinicius F.
;
Esmi, Estevao
;
Barros, Laecio C.
;
Barreto, GA
;
Coelho, R
Total Authors: 6
|
| Document type: | Journal article |
| Source: | FUZZY INFORMATION PROCESSING, NAFIPS 2018; v. 831, p. 12-pg., 2018-01-01. |
| Abstract | |
This work focus on the least square method to fit a fuzzy function to longitudinal data given by fuzzy numbers. In order to consider the intrinsic correlation of longitudinal data, we assume that there exits a linear relation among the involved fuzzy numbers that arises from the concept of a joint possibility distribution. We propose a numerical method to solve a fuzzy least square problem taking into account this linear correlation. To this end, we extend the classical least square method by means of the sup-J extension principle, which consists of a generalization of Zadeh's extension principle. Finally, we use our proposal method to fit a longitudinal dataset. (AU) | |
| FAPESP's process: | 16/26040-7 - Differential and integral calculus based on arithmetic of interactive fuzzy numbers |
| Grantee: | Estevão Esmi Laureano |
| Support Opportunities: | Regular Research Grants |