Premium
Aggregation of uncertainty data based on ordered weighting aggregation and generalized information quality
Author(s) -
Li Yuting,
Xiao Fuyuan
Publication year - 2019
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22111
Subject(s) - weighting , credibility , computer science , data mining , sensor fusion , ignorance , operator (biology) , quality (philosophy) , information fusion , process (computing) , fault (geology) , information quality , data quality , algorithm , mathematical optimization , artificial intelligence , information system , mathematics , engineering , philosophy , repressor , law , chemistry , operating system , biochemistry , political science , transcription factor , medicine , seismology , electrical engineering , gene , geology , operations management , metric (unit) , epistemology , radiology
It is necessary to take the information quality into consideration in information fusion. However, existing information quality has a limitation due to the ignorance of the credibility of information source. In this paper, the generalized information quality (GIQ) been proposed considering the association among the collected sensor reports, first. Then, the ordered weighting aggregation (OWA) operator of probability distribution based on the GIQ is presented. Numerical example and real application in fault diagnosis are used to illustrate the efficiency of the proposed method. The proposed GIQ and OWA algorithm has the advantage in fault tolerance and reduce the impact of conflict data in data fusion process, due to the consideration of the credibility of each sensor report. The proposed method has the promising aspects in uncertainty data aggregation.