Data-driven design of fuzzy system with relational input partition

An approach to data-driven linguistic modeling is presented. The methodology is based on a fuzzy system with relational input partition that allows for transparent modeling of linear dependencies between the inputs. An identification algorithm for this type of fuzzy system is proposed. It automatically finds the strongest dependencies from numerical data. An application example illustrates the usefulness of the proposed approach.