A new model for threat assessment in data fusion based on fuzzy evidence theory

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title A new model for threat assessment in data fusion based on fuzzy evidence theory
 
Creator Azimirad, Ehsan
Haddadnia, Javad
 
Subject Threat Assessment; Fuzzy Evidence Theory; Dempster- Shaffer Theory; Imperfect Information; Uncertainty Measures
 
Description In this paper a new method for threat assessment is proposed based on Fuzzy Evidence Theory. The most widely classical and intelligent methods used for threat assessment systems will be Evidence or Dempster Shafer and Fuzzy Sets Theories. The disadvantage of both methods is failing to calculate of uncertainty in the data from the sensors and the poor reliability of system. To fix this flaw in the system of dynamic targets threat assessment is proposed fuzzy evidence theory as a combination of both Dempster- Shafer and Fuzzy Sets Theories. In this model, the uncertainty in input data from the sensors and the whole system is measured using the best measure of the uncertainty. Also, a comprehensive comparison is done between the uncertainty of fuzzy model and fuzzy- evidence model (proposed method). This method applied to a real time scenario for air threat assessment. The simulation results show that this method is reasonable, effective, accuracy and reliability.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2016-07-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/56
10.26555/ijain.v2i2.56
 
Source International Journal of Advances in Intelligent Informatics; Vol 2, No 2 (2016): July 2016; 54-64
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/56/ijain_v2i2_p54_64
 
Rights Copyright (c) 2016 International Journal of Advances in Intelligent Informatics
http://creativecommons.org/licenses/by-sa/4.0
 

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