Name
Abstract | ||
|---|---|---|
•A novel contractor default prediction model is proposed.•The model is developed based on the SMOTE, LS-SVM, and DE algorithms.•Historical cases were collected to construct and verify the model.•Experimental results show that the model can deliver superior performance. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.knosys.2014.08.009 | Knowledge-Based Systems |
Keywords | Field | DocType |
Hybrid intelligence,Financial default prediction,Least Squares Support Vector Machine,Differential Evolution,Imbalanced classification | Data mining,Least squares support vector machine,Inference,Computer science,Supervised learning,Differential evolution,Construction industry,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
71 | 1 | 0950-7051 |
Citations | PageRank | References |
4 | 0.41 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min-Yuan Cheng | 1 | 174 | 19.84 |
| Nhat-Duc Hoang | 2 | 64 | 12.96 |
| Lisayuri Limanto | 3 | 4 | 0.41 |
| Yu-Wei Wu | 4 | 43 | 5.89 |