Published 1995
| Version v1
Miscellaneous
The fundamentals of fuzzy neural network and application in nuclear monitoring
Description
The authors presents a fuzzy modeling method using fuzzy neural network with the back-propagation algorithm. The new method can identify the fuzzy model of a nonlinear system automatically. Fuzzy neural network is used to generate fuzzy rules and membership functions. The feasibility and inferential statistic of the method is examined by using numerical data and XOR problem. The FNN improves accuracy and reliability, reduces design time and minimizes system cost of fuzzy design. The FNN can be used for estimation of human injury in nuclear explosions and can be simplified to a rule neural network (RNN), which is used for pole extraction of signal. Preliminary simulation show that FNN has vest vistas in nuclear monitoring
Additional details
Publishing Information
- Imprint Title
- Proceedings of the 8th national conference on computer application in science and technology
- Imprint Pagination
- 340 p.
- Journal Page Range
- p. 211-215, 223.
Conference
- Title
- 8. national conference on computer application in science and technology.
- Dates
- 27 Oct - 1 Nov 1995.
- Place
- Huangshan (China).
INIS
- Country of Publication
- China
- Country of Input or Organization
- China
- INIS RN
- 28005408
- Subject category
- S42: ENGINEERING; S99: GENERAL AND MISCELLANEOUS;
- Resource subtype / Literary indicator
- Conference, Non-conventional Literature
- Descriptors DEI
- ACCURACY; ALGORITHMS; FEASIBILITY STUDIES; FUZZY LOGIC; NEURAL NETWORKS; NUCLEAR EXPLOSION DETECTION; TESTING
- Descriptors DEC
- DETECTION; MATHEMATICAL LOGIC