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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259645
