Knowledge discovery based on neural networks

被引:26
作者
Fu, LM [1 ]
机构
[1] Univ Florida, Dept Comp Sci & Informat Engn, Gainesville, FL 32611 USA
关键词
D O I
10.1145/319382.319391
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The intelligence emerging from interactions among numerous self-organizing processing elements can be trained to discover the knowledge embedded in data.
引用
收藏
页码:47 / 50
页数:4
相关论文
共 7 条
[1]   Survey and critique of techniques for extracting rules from trained artificial neural networks [J].
Andrews, R ;
Diederich, J ;
Tickle, AB .
KNOWLEDGE-BASED SYSTEMS, 1995, 8 (06) :373-389
[2]   Knowledge discovery in reaction databases: Landscaping organic reactions by a self-organizing neural network [J].
Chen, LR ;
Gasteiger, J .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 1997, 119 (17) :4033-4042
[3]  
Fu L, 1994, NEURAL NETWORKS COMP
[4]   A neural-network model for learning domain rules based on its activation function characteristics [J].
Fu, LM .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1998, 9 (05) :787-795
[5]  
GILES CL, 1992, ADV NEURAL INFORMATI, V4
[6]   EFFECT OF NONCONTACTED BASES ON THE AFFINITY OF 434 OPERATOR FOR 434 REPRESSOR AND CRO [J].
KOUDELKA, GB ;
HARRISON, SC ;
PTASHNE, M .
NATURE, 1987, 326 (6116) :886-888
[7]   KNOWLEDGE-BASED ARTIFICIAL NEURAL NETWORKS [J].
TOWELL, GG ;
SHAVLIK, JW .
ARTIFICIAL INTELLIGENCE, 1994, 70 (1-2) :119-165