DocumentCode
1901101
Title
Case Retrieval Strategy Based on GAs and Group Decision-Making Method
Author
Jiang, Wei ; Yan, Ai-jun ; Wang, Pu
Author_Institution
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear
2010
fDate
25-26 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
Case retrieval is the focal stage in a Case-Based Reasoning (CBR) system. In this paper, a new case retrieval method called CRGCU is proposed in a systematical way, which is based on Genetic Algorithms (GAs) and Group Decision-Making method. First, feature attribute weights of cases are optimized by using GAs. Second, instead of utilizing only one set of feature attribute weights, we calculate similarity based on multiple sets of optimized weights. The result of case retrieval can be obtained at last by adopting Group Cardinal Utility function. The experiments on both static and dynamic data sets illustrate that our method is effective and suitable for CBR system.
Keywords
case-based reasoning; decision making; genetic algorithms; CRGCU; case based reasoning system; case retrieval strategy; genetic algorithms; group cardinal utility function; group decision making method; Accuracy; Cognition; Databases; Decision making; Gallium; Iris; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location
Wuhan
ISSN
2156-7379
Print_ISBN
978-1-4244-7939-9
Electronic_ISBN
2156-7379
Type
conf
DOI
10.1109/ICIECS.2010.5678347
Filename
5678347
Link To Document