Intuitionistic fuzzy seasonal variation analysis of marine biotoxin distribution in the Black Sea

Abstract

It is crucial to establish a seasonal dependence on the levels of marine biotoxins in the Black Sea to impose seasonal prohibitions on the gathering of marine species in this sea and safeguard human health. Fisher’s analysis of variance (ANOVA) is a statistical technique for assessing how various variables affect a collection of data. In some cases, research must be carried out in an uncertain environment, with missing or insufficient data. An approach for solving this imprecision when a data set occurs in an ambiguous context is intuitionistic fuzzy logic, which Atanassov introduced in 1983. Compared to fuzzy data, intuitionistic fuzzy (IF) data also has a hesitation degree. In 2020, we first suggested the one-way (1-D) IFANOVA and the software utility for its performance, combining traditional variational analysis with modeling opportunities of Index Matrices (IMs) and Intuitionistic Fuzzy Sets (IFSs). The current study focuses on 1-D IFANOVA of the distribution of marine biotoxins in the Black Sea by the “season” factor on the IF dataset of the number of marine biotoxins for the period from February 1 to July 31, 2021. We will also compare the findings of 1-D IFANOVA and conventional ANOVA performed on the identical data set.