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中国工业与应用数学学会会刊
主管:中华人民共和国教育部
主办:西安交通大学
ISSN 1005-3085  CN 61-1269/O1

工程数学学报 ›› 2019, Vol. 36 ›› Issue (1): 18-32.doi: 10.3969/j.issn.1005-3085.2019.01.002

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基于五 I 算法的模糊系统的响应能力

李军霞1,   李得超1,2   

  1. 1- 浙江海洋大学数理与信息学院,舟山  316022
    2- 浙江省海洋大数据挖掘与应用重点实验室,舟山  316022
  • 收稿日期:2017-06-08 接受日期:2017-11-29 出版日期:2019-02-15 发布日期:2019-04-15
  • 基金资助:
    国家自然科学基金(61673352).

Response Capability of Fuzzy Systems Based on Quintuple I Algorithm

LI Jun-xia1,  LI De-chao1,2   

  1. 1- School of Mathematics, Physics & Information Science, Zhejiang Ocean University, Zhoushan 316022
    2- Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhoushan 316022
  • Received:2017-06-08 Accepted:2017-11-29 Online:2019-02-15 Published:2019-04-15
  • Supported by:
    The National Natural Science Foundation of China (61673352).

摘要: 为了在实际中更好地应用基于五I算法的模糊系统,研究此类模糊系统的响应能力和泛逼近性意义非凡.本文首先给出基于S蕴涵和Zadeh蕴涵的五I算法的模糊推理表达式.本文指出对于S蕴涵和R蕴涵,采用单点模糊化、重心解模糊法、基于五I算法的单输入单输出(SISO)模糊系统只有阶跃输出条件而无函数逼近的泛性;而对Zadeh蕴涵,此类模糊系统不一定具有此性质.此外,在基于五I算法的多规则SISO模糊系统中,一定条件下模糊推理与聚合的次序无关.最后提供一个具体的例子来展示基于五I算法的模糊系统的响应能力和泛逼性.

关键词: 模糊推理, 模糊系统, 五I算法, 蕴涵算子, 响应函数

Abstract: In order to apply the fuzzy system based on the QIP algorithm well in practice, research on responsiveness and general approximation of such fuzzy systems is of great significance. In this paper, the fuzzy inference expression of 5-I algorithm based on S implication and Zadeh implication is proposed. Furthermore, by using single-point fuzzification and gravity center defuzzification method, we find that for S implication and R implication, a single-input single-output (SISO) fuzzy system based on QIP algorithm has only step output conditions and can not approximates a function well. The preceding property does not necessarily exist in such fuzzy systems with Zadeh implication. In addition, in the multi-rule SISO fuzzy system based on QIP algorithm, fuzzy reasoning is independent of the order of aggregation under certain conditions. Finally, a concrete example is provided to demonstrate responsiveness and universal approximation of fuzzy systems based on the five-I algorithm.

Key words: fuzzy reasoning, fuzzy system, quintuple I algorithm, implication operator, response function

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