A highly interpretable form of Sugeno inference systems

被引:45
作者
Bikdash, M [1 ]
机构
[1] N Carolina Agr & Technol State Univ, Dept Elect Engn, Greensboro, NC 27411 USA
关键词
fuzzy systems; piecewise polynomial approximation; spline functions;
D O I
10.1109/91.811237
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a new form of fuzzy inference systems (FIS) that is highly interpretable and easy to manipulate. The new 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 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.
引用
收藏
页码:686 / 696
页数:11
相关论文
共 24 条