A complete pattern recognition approach under Atanassov's intuitionistic fuzzy sets

被引：43

作者：

Chu, Chun-Hsiao ^{[1
]}

Hung, Kuo-Chen ^{[2
]}

Julian, Peterson ^{[3
]}

机构：

[1] Aletheia Univ, Dept Tourism, New Taipei City 25103, Taiwan

[2] Hungkuang Univ, Dept Comp Sci & Informat Management, Taichung 43302, Taiwan

[3] Cent Police Univ, Dept Traff Sci, Kueishan Hsiang 33304, Taoyuan County, Taiwan

来源：

KNOWLEDGE-BASED SYSTEMS | 2014年 / 66卷

关键词：

Fault diagnosis; Atanassov's intuitionistic fuzzy sets (AIFSs); Similarity measure; Pattern recognition; Turbine generators; RESTRICTED EQUIVALENCE FUNCTIONS; MITCHELL SIMILARITY MEASURE; FAULT-DIAGNOSIS; DECISION-MAKING; VAGUE SETS; SYSTEM;

D O I：

10.1016/j.knosys.2014.04.014

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This research is aimed at developing a method for solving pattern recognition problems under the Atanassov's intuitionistic fuzzy sets based on similarity measures. First we proposed two similarity measures and then developed a method based on our similarity measures. We also proved that our method is able to solve the pattern recognition problems. Finally, a fault diagnosis example of the turbine vibration has been examined by our method. The example demonstrates that the proposed method cannot only diagnose the main faults of the turbine generator but also it can detect useful information for future trends and multi-fault analysis. In addition, for the convenience of computing and ranking processes, a computer interface decision support system is also developed to help decision maker make diagnoses more efficiently. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：36 / 45

页数：10

共 26 条

[1]

[Anonymous], 2010, Intuitionistic Fuzzy Sets: Theory and Applications

[2] INTUITIONISTIC FUZZY-SETS [J].