Evolutionary Fuzzy Case-based Reasoning for Financial Performance Ranking
- Sheng-Tun Li 0, Hei-Fong Ho, Yi-Chung Cheng
- Corresponding Author
- Sheng-Tun Li
0National Cheng Kung University
Available Online undefined NaN.
- https://doi.org/10.2991/jcis.2006.141How to use a DOI?
- Case-Based Reasoning, Genetic Algorithms, Fuzzy Nearest Neighbor algorithm, financial statement analysis, financial performance ranking.
- we propose a hybrid decision model for supporting the ranking financial status of corporations using case-based reasoning augmented with genetic algorithms and the fuzzy nearest neighbor method. An empirical experimentation on 746 cases was conducted that shows that the average accuracy of the ranking is about 92% and 80% for the first order and the second order, respectively.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Sheng-Tun Li AU - Hei-Fong Ho AU - Yi-Chung Cheng PY - NaN/NaN DA - NaN/NaN TI - Evolutionary Fuzzy Case-based Reasoning for Financial Performance Ranking BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.141 DO - https://doi.org/10.2991/jcis.2006.141 ID - LiNaN/NaN ER -