Login / Signup

Intuitionistic fuzzy set of Γ -submodules and its application in modeling spread of viral diseases, mutated COVID- n , via flights.

Narjes FirouzkouhiAbbas AminiChun ChengAli ZarrabiBijan Davvaz
Published in: International journal of intelligent systems (2021)
In this study, we generalize fuzzy Γ -module, as intuitionistic fuzzy Γ -submodule of Γ -module (IF Γ M), and utilize it for modeling the spread of coronavirus in air travels. Certain fundamental features of intuitionistic fuzzy Γ -submodule are provided, and it is proved that IF Γ M can be considered as a complete lattice. Some elucidatory examples are demonstrated to explain the properties of IF Γ M. The relevance between the upper and lower α -level cut and intuitionistic fuzzy Γ -submodules are presented and the characteristics of upper and lower under image and inverse image of IF Γ M are acquired. It is verified that the image and inverse image of intuitionistic fuzzy Γ -submodule are preserved under the module homomorphism. The obtained IF Γ M is used to model the aerial transition of viral diseases, that is, COVID- n , via flights.
Keyphrases
  • sars cov
  • neural network
  • deep learning
  • coronavirus disease
  • machine learning