Amalgamation of knowledge and data through fuzzy modelling

Abstract

Typically, two sources of information about a system are available: some artisan knowledge and a sample of input-output data. This paper proposes a method for the amalgamation of these to synthesise a fuzzy model of the system. The artisan knowledge will likely be qualitative, of low resolution and accuracy whilst the data sample noisy and incomplete (not comprehensively covering the whole input space). A model derived from the union of these is potentially superior to one developed from either alone.