Abstract
In this manuscript we propose a method to fit a dataset with uncertainty. These data are described by interactive fuzzy numbers. The relationship of interactivity is associated with the notion of joint possibility distribution. We focus on a specific type of interactivity namely linear interactivity. We use this concept to introduce a class of fuzzy numbers called quasi linearly interactive fuzzy numbers. We provide an application to fit a dataset of the HIV disease to illustrate the proposed method.
Cite
CITATION STYLE
Pinto, N. J. B., Esmi, E., Wasques, V. F., & Barros, L. C. (2019). Least Square Method with Quasi Linearly Interactive Fuzzy Data: Fitting an HIV Dataset. In Advances in Intelligent Systems and Computing (Vol. 1000, pp. 177–189). Springer Verlag. https://doi.org/10.1007/978-3-030-21920-8_17
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