A normalized fuzzy neural network and its application

被引：0
|
作者：
Shang, FH [1 ]
Zhao, TJ [1 ]
Li, S [1 ]
机构：
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
来源：
2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS | 2003年
关键词：
fuzzy neural network; normalization; water-flooded zone identification;
D O I：
10.1109/ICMLC.2003.1259645
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1088 / 1091
页数：4
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