DocumentCode :
2375138
Title :
A hybrid method for effective management of the uncertainty in army decision making using cognitive agents and Classification based on Fuzzy Association Rules
Author :
Heravi, Mojtaba ; Akramizadeh, Ali ; Pourakbar, Mohammadreza ; Menhaj, M.B.
Author_Institution :
Cognitive Sci. & Artificial Intell. Lab., Inst. for Biol. Sci., Tehran, Iran
fYear :
2013
fDate :
27-29 Aug. 2013
Firstpage :
1
Lastpage :
6
Abstract :
Decision making is an important problem in most of the army operations. One of the challenging issues in this area is uncertainty in wars with uncertain information which causes many destructive effects on the results of strategies in battlefields. Cognitive Agent (CA) brings about an improvement by reducing the uncertainties meanwhile causes some unavoidable negative effects in critical decisions. Classification based on Fuzzy Association Rules (CFAR) is an effective method for rule mining which has the ability to deal with Sharp Boundary problems due to its flexibility in quantitative attribute domains and therefore it reduces the uncertainty. In this article a new hybrid method is proposed to reduce the uncertainty in decision making based on CA and CFAR. Simulation results show that the proposed method provides more understandable and has lower risk and more precise and flexibility as it reduces the generated rules.
Keywords :
data mining; decision making; decision support systems; fuzzy set theory; military computing; multi-agent systems; pattern classification; CA; CFAR method; army decision making; classification based on fuzzy association rules; cognitive agents; quantitative attribute domains; rule mining; sharp boundary problems; uncertainty management; Asymmetric Warfare; Classification based on Fuzzy Association Rules; Cognitive Agent; Decision Making; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (IFSC), 2013 13th Iranian Conference on
Conference_Location :
Qazvin
Print_ISBN :
978-1-4799-1227-8
Type :
conf
DOI :
10.1109/IFSC.2013.6675655
Filename :
6675655
Link To Document :
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