Interpolation and extrapolation of fuzzy quantities – the multiple-dimensional case

被引：31

作者：

S. Jenei

E. P. Klement

R. Konzel

机构：

[1] Institute of Mathematics and Informatics,

[2] University of Pécs,undefined

[3] Ifjúság u. 6,undefined

[4] H-7624 Pécs,undefined

[5] Hungary e-mail: jenei@ttk.pte.hu,undefined

[6] Department of Algebra,undefined

[7] Stochastic and Knowledge-Based Mathematical Systems,undefined

[8] Johannes Kepler University,undefined

[9] A-4040 Linz,undefined

[10] Austria e-mails: sandor@flll.uni-linz.ac.at,undefined

[11] klement@flll.uni-linz.ac.at,undefined

[12] richard@flll.uni-linz.ac.at,undefined

来源：

Soft Computing | 2002年 / 6卷 / 3期

关键词：

Keywords Fuzzy sets, Knowledge-based systems, Interpolation/extrapolation, Sparse rule base, Approximate reasoning;

D O I：

10.1007/s005000100152

中图分类号：

学科分类号：

摘要：

This paper deals with the problem of rule interpolation and rule extrapolation for fuzzy and possibilistic systems. Such systems are used for representing and processing vague linguistic If-Then-rules, and they have been increasingly applied in the field of control engineering, pattern recognition and expert systems. The methodology of rule interpolation is required for deducing plausible conclusions from sparse (incomplete) rule bases. The interpolation/extrapolation method which was proposed for one-dimensional input space in [4] is extended in this paper to the general n-dimensional case by using the concept of aggregation operators. A characterization of the class of aggregation operators with which the extended method preserves all the nice features of the one- dimensional method is given.

引用

页码：258 / 270

页数：12