Improvement of time forecasting models using a novel hybridization of bootstrap and double bootstrap artificial neural networks
Hybrid models such as the Artificial Neural Network-Autoregressive Integrated Moving Average (ANN–ARIMA) model are widely used in forecasting. However, inaccuracies and inefficiency remain in evidence. To yield the ANN–ARIMA with a higher degree of accuracy, efficiency and precision, the bootstrap a...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2019
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| Subjects: |