Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
487979 | Procedia Computer Science | 2013 | 6 Pages |
Abstract
The following paper discusses the use of a hybrid model for the prediction of short-term US interest rates. The model consists of a differential evolution-based fuzzy type-2 clustering with a fuzzy type-2 inference neural network, after input preprocessing with multiple regression analysis. The model was applied to forecast the US 3- Month T-bill rates. Promising model performance was obtained as measured using root mean square error.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)