Interval-valued fuzzy reasoning algorithms based on Schweizer-Sklar t-norms and its application

被引：7

作者：

Luo, Minxia ^{[1
]}

Zhao, Ruirui ^{[2
]}

Liu, Bei ^{[1
]}

Liang, Jingjing ^{[1
]}

机构：

[1] China Jiliang Univ, Dept Informat & Comp Sci, Hangzhou 310018, Peoples R China

[2] Shaanxi Normal Univ, Coll Math & Informat Sci, Xian 710062, Peoples R China

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2020年 / 87卷

基金：

中国国家自然科学基金;

关键词：

Interval-valued fuzzy sets; Schweizer-Sklar t-norms; Triple I algorithms; Normalized Minkowski distance; Robustness; DELTA-EQUALITIES; ROBUSTNESS; INFERENCE; OPERATORS; SYSTEMS; SETS;

D O I：

10.1016/j.engappai.2019.103313

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Based on the normalized Minkowski distance in Hausdorff metrics, we study the sensitivity of interval-valued Schweizer-Sklar t-norms and their corresponding residual implications. Moreover, we investigate the robustness of interval-valued fuzzy reasoning triple I algorithms based on Schweizer-Sklar operators and illustrate the feasibility of the algorithms by a numerical example. Finally, the interval-valued fuzzy reasoning triple I algorithms are applied to medical diagnosis.

引用

页数：7

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