A Mathematical Fuzzy Transform for Evaluating the Effect of Recombi Nant on Growth Hormone

Abstract

The fuzzy transform (FT) is a novel, extensively utilized soft computing method with solid mathematical underpinnings. This article presents the technique using data on plasma levels of Interleukin-6, which is indicative of low-grade inflammation or severe activity. We first show how useful it is for describing and identifying attribute dependencies. Moreover, we use it to connection mining of a functional kind. Moreover, the fuzzy membership values that have been found are specified linguistically, which means that fuzzy transforms make up their antecedent, and only evaluative linguistic terms characterize their consequent.