DocumentCode :
1571895
Title :
Attribute fusion based on NFE model and convex optimization approach
Author :
Liu, Mei ; Quan, Taifan ; Zhao, Lei
Author_Institution :
Dept. of Electron. Eng., Harbin Inst. of Technol., China
Volume :
4
fYear :
2004
Firstpage :
3165
Abstract :
Due to the drawbacks of D-S evidential inference theory approach such as difficulty of obtaining basic probability assignments, the need of being exhaustive and exclusive evidence of the reports, and a computational complexity suffering from an exponential growth, an attribute fusion structure based on NFE (neural fuzzy expert) model and convex approach is presented. This paper also presented how to make sensor reports with fuzzy expert system and acquire the reliability of sensors with fuzzy neural network. The method to fusion sensor reports with convex optimization approach is also discussed. This method makes good use of the logic reasoning ability of fuzzy expert system and the self-learning, self-reasoning ability of fuzzy neural network. The fusion results show that these methods can fusion efficiently in real time with the more reliable results.
Keywords :
convex programming; expert systems; fuzzy neural nets; inference mechanisms; probability; sensor fusion; Dempster-Shafer theory; attribute fusion; basic probability assignments; convex optimization; evidential inference theory; fuzzy expert system; fuzzy neural network; Computational complexity; Electronic mail; Expert systems; Fuzzy logic; Fuzzy neural networks; Hybrid intelligent systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1343105
Filename :
1343105
Link To Document :
بازگشت