Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4946070 | Knowledge-Based Systems | 2017 | 38 Pages |
Abstract
We demonstrate that the proposed temporal CBR system is able to detect the different proposed risk scenarios when there is a large number of cases. That is, the CBR systems are useful in the long term. Experiments indicate that the temporal CBM algorithms analysed are able to reduce case-bases successfully to detect abnormal scenarios. However, success in creating a maintained case-base equivalent to the original depends on the number of cases.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Eduardo Lupiani, Jose M. Juarez, Jose Palma, Roque Marin,