摘要
本文首先把SIS算法与区间值模糊集相结合,提出了基于区间值模糊推理SIS算法,并给出了该算法解的表达形式。其次,提出区间值模糊集相似度的概念,并基于此研究了区间值模糊推理SIS算法的鲁棒性。结论表明在区间值模糊集上SIS算法解的相似度量的不等式定理是模糊集上SIS算法相关结论的一般形式。
At first,the paper combines SIS algorithm with interval-valued fuzzy set,and proposes the SIS algorithm based on interval-valued fuzzy reasoning,then gives the expressions of the solution of this algorithm.Secondly,the definition of similarity based on interval-valued is proposed.And the robustness of interval-value fuzzy inference SIS algorithm is studied.It is shown that the inequality theorems of similarity measurement of interval-value fuzzy inference SIS algorithm is the general form of the conclusions of SIS algorithm in fuzzy sets.
作者
王蓉
惠小静
井美
WANG Rong;HUI Xiao-jing;JING Mei(College of Mathematics and Computer Science,Yan’an University,Yan'an 716000,China)
出处
《模糊系统与数学》
北大核心
2018年第5期41-46,共6页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(11471007)
延安大学研究生创新基金资助项目
关键词
区间值模糊推理
相似度
SIS算法
鲁棒性
Interval-valued Fuzzy Inference
Similarity
SIS Algorithm
Robustness
