Proceedings of the Third International Conference on Control, Automation and Systems Engineering (CASE-13)

Research on Optimization of Case-Based Reasoning System

Authors
Lin Tong, Di Wu
Corresponding Author
Lin Tong
Available Online August 2013.
DOI
https://doi.org/10.2991/case-13.2013.9How to use a DOI?
Keywords
CBR; optimization; clustering algorithm; case retrieval
Abstract
In this paper the deduction and optimization scheme is proposed for CBR decision making system. The CBR system is improved by using CURE_KNN algorithm. Cases in the library are clustered into some subsets, and the standard case library is constructed in a hierarchical manner. After the similarity between the target case and the central index point of each subset is computed, the nearest neighbor is used for retrieval in the nearest neighbor subset. The case library is maintained with the case addition and deletion strategy based on clustering. The performance of the CBR system is improved by the above multiple optimization strategy. At last the efficiency and availability of the proposed scheme is verified with system test.
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Proceedings
Third International Conference on Control, Automation and Systems Engineering (CASE-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-81-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/case-13.2013.9How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Lin Tong
AU  - Di Wu
PY  - 2013/08
DA  - 2013/08
TI  - Research on Optimization of Case-Based Reasoning System
BT  - Third International Conference on Control, Automation and Systems Engineering (CASE-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/case-13.2013.9
DO  - https://doi.org/10.2991/case-13.2013.9
ID  - Tong2013/08
ER  -