Qiokata, Viliame and Khan, Mohammad G.M. (2015) Artificial neural network and regression models for predicting Fiji population. [Conference Proceedings]
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The paper compares Artificial Neural Network (ANN) model against traditional models in the modeling of population and external migration for Fiji population components during the years from 1986 to 2012. The performance of the various models used are based on the values of the various error functions such as the R-squared (R2), Root Square Mean Error (RSME), Mean Absolute Error (MAE), Standard Error of Regression (SER), Sum Squared Residual (SSR), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Across yearly time series, ANN performed better than those traditional models, when comparing the various error functions used.
| Item Type: | Conference Proceedings |
|---|---|
| Additional Information: | DOI: 10.1109/APWCCSE.2014.7053850 |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HB Economic Theory |
| Divisions: | College of Foundation Studies Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences |
| Depositing User: | Fulori Nainoca - Waqairagata |
| Date Deposited: | 16 Mar 2015 00:34 |
| Last Modified: | 15 Mar 2017 03:48 |
| URI: | https://repository.usp.ac.fj/id/eprint/8127 |
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