Fuzzy inference systems for mineral exploration

Abstract

A Fuzzy Inference System (FIS) is a system containing a set of if-then rules expressed in natural language to simulate inductive reasoning of an expert (Porwal et al. 2015). It is a knowledge-driven inference engine built upon the theory of fuzzy sets. A fuzzy set is the extension of a classical set and does not have clearly defined limits. The degree of membership to fuzzy sets grades from 0 to 1 (unlike classical sets, where it is either 0 or 1) (Zadeh 1973). A fuzzy set, hence, allows for a simplified representation of real-world phenomena including geological processes (see “Fuzzy Set Theory in Geosciences”). When more than one fuzzy set are identified in a dataset and combined using logical operators, it forms a fuzzy logic overlay. Numerous fuzzy logic overlays expressed as if-thenrules and integrated in an inference engine encompass a FIS. A FIS has the capabilities to capture the imprecision and vagueness of natural phenomena within a single system