DocumentCode
401616
Title
A normalized fuzzy neural network and its application
Author
Shang, Fu-hua ; Zhao, Tie-jun ; Li, Sheng
Author_Institution
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., China
Volume
2
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
1088
Abstract
A normalized fuzzy neural network (NFNN) with five layers is proposed. Focusing on the structure optimization of network, a new node selection method and corresponding back propagation learning algorithm rules are presented. In the case of with fewer input nodes, the training is faster in this kind of neural network. The proposed method is applied successfully to water-flooded zone identification in measure-well explanation, which is an important problem in the oil field development. Test results illustrate its practicability.
Keywords
backpropagation; fuzzy neural nets; geophysics computing; identification; petroleum industry; back propagation learning algorithm rules; node selection method; normalized fuzzy neural network; oil field development; water-flooded zone identification; Computer networks; Electronic mail; Fuzzy logic; Fuzzy neural networks; Input variables; Intelligent networks; Intelligent systems; Neural networks; Optimization methods; Petroleum;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259645
Filename
1259645
Link To Document