Fuzzy Information Fusion for Hypergame Outcome Preference Perception

2006 ◽  
pp. 882-887
Author(s):  
Yexin Song ◽  
Zhijun Li ◽  
Yongqiang Chen
Keyword(s):  
Information Fusion ◽  
Fuzzy Information

Developing the modified R-numbers for risk-based fuzzy information fusion and its application to failure modes, effects, and system resilience analysis (FMESRA)

2020 ◽  
Author(s):  
Hamidreza Seiti ◽  
Mahdi Fathi ◽  
Ashkan Hafezalkotob ◽  
Enrique Herrera-Viedma ◽  
Ibrahim A. Hameed
Keyword(s):  
Information Fusion ◽  
Failure Modes ◽  
Fuzzy Information ◽  
System Resilience

Research on Fault Diagnosis Strategy of Belt Conveyor

2013 ◽  
Vol 312 ◽  
pp. 607-610 ◽  
Author(s):  
Wei Hu ◽  
Ou Li
Keyword(s):  
Fault Diagnosis ◽  
Set Theory ◽  
Information Fusion ◽  
Accurate Diagnosis ◽  
Experimental Result ◽  
Fusion Center ◽  
Fusion Technology ◽  
Fuzzy Information ◽  
Belt Conveyor ◽  
Diagnosis Method

In view of the inadequacy of the fault diagnosis of the belt conveyor, the paper takes advantage of the application of fuzzy information fusion technology to fault diagnosis, based on the fuzzy set theory, a fault diagnosis method based on Multi-sensor fuzzy information fusion is developed. The obtain information of many sensors will fuzzy, again its fusion based on the synthetic operation and decision-making rules of the fusion center, in order to gain the accurate state estimation and judgment of belt conveyor. The experimental result indicates that the credibility of diagnosis is improved markedly and the uncertainty is reduced significantly after the multi-sensor fuzzy information fusion, the accurate diagnosis to belt conveyor is realized.

scholarly journals Automatic brain tumor extraction using fuzzy information fusion

2002 ◽  
Author(s):  
Weibei Dou ◽  
Qingmin Liao ◽  
Su Ruan ◽  
Daniel Bloyet ◽  
Jean-Mac Constans ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Information Fusion ◽  
Fuzzy Information ◽  
Tumor Extraction

scholarly journals Hesitant Fuzzy Generalised Bonferroni Mean Operators Based on Archimedean Copula for Multiple-Attribute Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ju Wu ◽  
Fang Liu ◽  
Yuan Rong ◽  
Yi Liu ◽  
Chengxi Liu
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Information Fusion ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Archimedean Copula ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Operation Rules ◽  
Multiple Attribute

Information fusion is an important part of multiple-attribute decision-making, and aggregation operator is an important tool of decision information fusion. Integration operators in a variety of fuzzy information environments have a slight lack of consideration for the correlation between variables. Archimedean copula provides information fusion patterns that rely on the intrinsic relevance of information. This paper extends the Archimedean copula to the aggregation of hesitant fuzzy information. Firstly, the Archimedean copula is used to generate the operation rules of the hesitant fuzzy elements. Secondly, the hesitant fuzzy copula Bonferroni mean operator and hesitant fuzzy weighted copula Bonferroni mean operator are propounded, and several properties are proved in detail. Furthermore, a decision-making method based on the operators is proposed, and the specific decision steps are given. Finally, an example is presented to illustrate the practical advantages of the method, and the sensitivity analysis of the decision results with the change of parameters is carried out.

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