Tactic of Case Retrieval Based on Rough Set Theory and Artificial Neural Network

被引：0

作者：

Deng, Wu ^{[1
]}

Guo, Fajun ^{[1
]}

Feng, Chao ^{[1
]}

机构：

[1] Dalian Jiaotong Univ, Software Inst, Dalian 116028, Peoples R China

来源：

PROCEEDINGS OF THE 2010 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND SCIENTIFIC MANAGEMENT, VOLS 1-2 | 2010年

关键词：

rough set theory; artificial neural network; case retrieval; case-based reasoning; feature vector;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In order to improve efficiency and quality of case retrieval in case-based reasoning system, a case retrieval model based on the integration of rough set theory and artificial neural network is presented. The paper analyzes and deals with case database using rough set theory in order to obtain the minimum case feature subset which is regarded as the inputs of RBF neural network for training the network. The pretreated requirement problem is inputted the optimized network model to find out the nearest case that is the design plan for design reference.

引用

页码：864 / 867

页数：4