| Texto completo | |
| Autor(es): |
Pinto, Nilmara J. B.
;
Wasques, Vinicius F.
;
Esmi, Estevao
;
Barros, Laecio C.
;
Barreto, GA
;
Coelho, R
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | FUZZY INFORMATION PROCESSING, NAFIPS 2018; v. 831, p. 12-pg., 2018-01-01. |
| Resumo | |
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) | |
| Processo FAPESP: | 16/26040-7 - Cálculo diferencial e integral baseado aritmética de números fuzzy interativos |
| Beneficiário: | Estevão Esmi Laureano |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |