Name
Abstract | ||
|---|---|---|
•The ANN-(U-)MIDAS model is developed.•It models artificial neural network on mixed frequency data via (U-)MIDAS.•It can be estimated by the standard gradient based optimization algorithm.•It is flexible to explore potential nonlinear patterns among variables.•It has been successfully applied to better Chinese inflation forecasts. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2018.10.013 | Expert Systems with Applications |
Keywords | Field | DocType |
Artificial neural network,Mixed frequency data,Mixed data sampling (MIDAS),Nonlinear pattern,Inflation forecasting | Data mining,Monte Carlo method,Nonlinear system,Mixed-data sampling,Intelligent decision support system,Computer science,Nonlinear programming,Preprocessor,Artificial neural network,Backpropagation | Journal |
Volume | ISSN | Citations |
118 | 0957-4174 | 1 |
PageRank | References | Authors |
0.36 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qifa Xu | 1 | 19 | 7.02 |
| Xingxuan Zhuo | 2 | 1 | 0.36 |
| cuixia jiang | 3 | 13 | 6.19 |
| Yezheng Liu | 4 | 145 | 24.69 |