Paper Info
Title
Asymmetric Closeness In Early Warning Radar Intelligence Quality Evaluation
Abstract
This paper proposes a novel asymmetric closeness degree approach for early warning radar(EWR) intelligence quality evaluation. Firstly, the evaluation indexes system is set up based on analyzing the main influencing factors, the practice of evaluating intelligence quality of radar troops, and the radar intelligence production processing and its characteristics. And then, the corresponding assessing model is designated, and the factors set, comment set and weight set are established according to the requirement of the evaluation. Finally, we analyze the quality of the EWR intelligence based on the contrast of using the maximum membership degree fuzzy comprehensive evaluation method, and using symmetric closeness degree and the asymmetric closeness degree method. The experiments show that the asymmetric closeness degree method is more effective to take comprehensive evaluations of a certain quality of EWR intelligence, and is helpful for finding out the factors which determine the quality of the radar intelligence.
Year
DOI
Venue
2018
10.1109/ICSAI.2018.8599460
2018 5TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI)
Keywords
Field
DocType
early warning radar, quality of intelligence, maximum membership degree, asymmetric closeness degree
Radar,Data mining,Computer science,Closeness,Early-warning radar,Fuzzy logic,Control engineering
Conference
ISSN
Citations 
PageRank 
2474-0217
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Renzheng Liu100.34
Kangsheng Tian200.68
Hongquan Li322.62
Shanchao Yang4113.88
Li Cai503.04