Research on Optimization of Case-Based Reasoning System

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lin Tong
AU  - Di Wu
PY  - 2013/08
DA  - 2013/08
TI  - Research on Optimization of Case-Based Reasoning System
BT  - Proceedings of the Third International Conference on Control, Automation and Systems Engineering (CASE-13)
PB  - Atlantis Press
SP  - 34
EP  - 37
SN  - 1951-6851
UR  - https://doi.org/10.2991/case-13.2013.9
DO  - 10.2991/case-13.2013.9
ID  - Tong2013/08
ER  -