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基于区间值相似度的加权模糊推理 被引量:1

Weighted Fuzzy Reasoning Based on Interval Value Similarity Measure
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摘要 在相似度的方法用于区间值模糊推理的过程中,为合理地计算区间值加权模糊产生式规则的输入事实与规则前件之间的相似度,给出区间值相似度的计算公式.在此基础上提出基于区间值相似度的加权模糊推理算法.为体现规则前件断言对于规则结果的重要性程度,在区间值模糊产生式规则中加入了权值参数.为了采用该算法,给出区间值排序的方法.最后用实例说明所给出的推理算法更符合实际需要,可操作性强,便于应用. In the fuzzy inference method, similarity-based fuzzy reasoning method is a kind of simple and im- portant method. This method is used for the interval valued fuzzy inference process. For the purpose of calculat- ing the similarity measure between the input facts and antecedent portion of the interval value weighted fuzzy production rules, interval value similarity measure calculation formula is proposed. On the basis of the interval valued similarity measure, a weighted fuzzy reasoning algorithm is proposed. The weight parameter is added to the interval valued fuzzy production rules to reflect the importance degree of the antecedent assertion for the reasoning result. In order to use the algorithm, a kind of interval value ranking method is proposed. Finally, an example is illustrate to show the proposed reasoning algorithm is more consistent with the actual needs, strong operability and convenient for application.
作者 孙晓玲 SUN Xiao-ling(School of Mathematics and Statistics, Hefei Normal University, Hefei Anhui 230601, China)
出处 《淮阴师范学院学报(自然科学版)》 CAS 2016年第3期193-198,共6页 Journal of Huaiyin Teachers College;Natural Science Edition
基金 安徽省高校自然科学研究重点资助项目(KJ2016A580)
关键词 区间值模糊产生式规则 区间值相似度 加权模糊推理 区间值模糊推理 区间值排序 interval valued fuzzy production rules interval value similarity measure weighted fuzzy reason-ing interval valued fuzzy reasoning interval value ranking
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