Title :
A highly interpretable form of Sugeno inference systems
Author_Institution :
Dept. of Electr. Eng., North Carolina A&T State Univ., Greensboro, NC, USA
fDate :
12/1/1999 12:00:00 AM
Abstract :
We present a form of fuzzy inference systems (FISs) that is highly interpretable and easy to manipulate. The form is based on a judicious choice of membership functions that have strong locality and differentiability properties and on a modification of the Sugeno and generalized Sugeno forms of the consequent polynomials so as to make them rule centered. Under these conditions, the coefficients in the consequent polynomials can be exactly interpreted as Taylor series coefficients. Besides the intuitive interpretation thus bestowed on the coefficients, we show that the new form allows easy design, manipulation, testing, training, and combination of the resulting fuzzy inference systems. The rudiments of a calculus of fuzzy inference systems are then introduced
Keywords :
fuzzy systems; inference mechanisms; piecewise polynomial techniques; polynomials; series (mathematics); splines (mathematics); Sugeno inference systems; Taylor series coefficients; consequent polynomials; differentiability; fuzzy inference systems; highly interpretable form; locality; membership functions; Calculus; Engines; Fuzzy sets; Fuzzy systems; Genetic algorithms; Neural networks; Polynomials; Spline; System testing; Taylor series;
Journal_Title :
Fuzzy Systems, IEEE Transactions on