Fuzzy Inference Method Based on Interval-Valued Similarity Measure

SHI Hong-yan; LUO Min-xia

doi:10.12263/DZXB.20211085

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Fuzzy Inference Method Based on Interval-Valued Similarity Measure

PAPERS | 更新时间：2025-12-08

- Fuzzy Inference Method Based on Interval-Valued Similarity Measure
- ACTA ELECTRONICA SINICA Vol. 50, Issue 11, Pages: 2738-2745(2022)
- 作者机构：
  
  中国计量大学理学院，浙江杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20211085
  CLC： O141.1
- Received：13 August 2021，
  
  Revised：2022-01-10，
  
  Published：25 November 2022
- 稿件说明：
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史宏艳,罗敏霞.基于区间值相似度的模糊推理算法[J].电子学报,2022,50(11):2738-2745.

SHI Hong-yan,LUO Min-xia.Fuzzy Inference Method Based on Interval-Valued Similarity Measure[J].ACTA ELECTRONICA SINICA,2022,50(11):2738-2745.
史宏艳,罗敏霞.基于区间值相似度的模糊推理算法[J].电子学报,2022,50(11):2738-2745. DOI： 10.12263/DZXB.20211085.

SHI Hong-yan,LUO Min-xia.Fuzzy Inference Method Based on Interval-Valued Similarity Measure[J].ACTA ELECTRONICA SINICA,2022,50(11):2738-2745. DOI： 10.12263/DZXB.20211085.

摘要

模糊推理最基本的模型是模糊假言推理和模糊反驳推理. 本文是在区间值模糊集层面解决区间值模糊假言推理和区间值模糊反驳推理问题，给出基于区间值相似度的模糊推理算法. 首先，基于区间值

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44117719&type=

http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=44117729&type=

1.01600003

2.28600001

-可表示三角范数诱导的区间值剩余蕴涵

给出一种区间值相似度；其次，研究基于区间值相似度的模糊推理算法，给出算法解的表示形式；证明基于区间值相似度的模糊推理算法具有还原性；最后，研究基于区间值相似度的广义模糊推理算法. 本文提出的基于区间值相似度的模糊推理算法可应用于模式识别与多属性决策等领域.

Abstract

The basic models of fuzzy reasoning are fuzzy modus ponens and fuzzy modus tollens. The paper studies the problems of interval-valued fuzzy modus ponens and interval-valued fuzzy modus tollens at the level of interval-valued fuzzy sets

and propose fuzzy reasoning algorithms based on interval-valued similarity measure. Based on the interval-valued residuated implication induced by left-continuous interval-valued

-representable triangular norm

the interval-valued similarity measure is given. The fuzzy reasoning algorithms based on interval-valued similarity are further studied

and the representation of the algorithm solutions are given. Meanwhile

the fuzzy reasoning algorithms based on interval-valued similarity are proved to be reductive. Finally

the generalized fuzzy reasoning algorithms based on interval-valued similarity measure are studied. The fuzzy reasoning algorithms based on interval-valued similarity measure can be applied to the fields of pattern recognition and multi-attribute decision-making.

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references

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Hong-yan SHI

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College of Sciences， China Jiliang University

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