NDLI: Application of BPNN and CBR on Fault Diagnosis for Missile Electronic Command System

Content Provider	IEEE Xplore Digital Library
Author	Jiu-ling Zhao Jiu-fen Zhao
Copyright Year	2006
Description	Author affiliation: Second Artillery Eng. Inst., Xi'an (Jiu-ling Zhao)
Abstract	Based on the complexity of the mobile missile electronic command system (MMECS), applying the single method in system fault diagnosis can hardly achieve satisfactory results. The fault diagnosis system combining the BP neural network (BPNN) method and the case-based reasoning (CBR) method was presented. The framework of the mixed neural network and the case presentation was put forward. The question of redundancy reasoning was solved, moreover, it can interpret the diagnoses by providing the successful case. Finally, with the example of voice interrupt, the system's correctness and validity was proved. It is shown that the system is suitable for both the operators training and online decision making for the army
Starting Page	5796
Ending Page	5799
File Size	120009
Page Count	4
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1714187
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Missiles Neural networks Weapons Artificial neural networks Multi-layer neural network Redundancy Decision making Inference mechanisms !Fault diagnosis Neural Network Missile electronic command system CBR
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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