Name
Title | ||
|---|---|---|
A hybrid model for bankruptcy prediction using genetic algorithm, fuzzy c-means and mars |
Abstract | ||
|---|---|---|
Bankruptcy prediction is very important for all the organization since it affects the economy and rise many social problems with high costs. There are large number of techniques have been developed to predict the bankruptcy, which helps the decision makers such as investors and financial analysts. One of the bankruptcy prediction models is the hybrid model using Fuzzy C-means clustering and MARS, which uses static ratios taken from the bank financial statements for prediction, which has its own theoretical advantages. The performance of existing bankruptcy model can be improved by selecting the best features dynamically depend on the nature of the firm. This dynamic selection can be accomplished by Genetic Algorithm and it improves the performance of prediction model. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.5121/ijsc.2011.2102 | Clinical Orthopaedics and Related Research |
Keywords | Field | DocType |
genetic algorithm,prediction model,artificial intelligent,evolutionary computing,decision maker,social problems | Data mining,Mars Exploration Program,Computer science,Fuzzy logic,Bankruptcy prediction,Bankruptcy,Artificial intelligence,Cluster analysis,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
abs/1103.2 | 1 | International Journal on Soft Computing (IJSC), Vol.2, No.1,
February 2011 |
Citations | PageRank | References |
3 | 0.40 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Martin | 1 | 11 | 2.32 |
| V. Gayathri | 2 | 3 | 0.40 |
| G. Saranya | 3 | 3 | 0.40 |
| P. Gayathri | 4 | 3 | 1.07 |
| V. Prasanna Venkatesan | 5 | 3 | 0.74 |