| Autor: |
Yurdusev, M. A., Firat, M., Mermer, M., Turan, M. E. |
| Předmět: |
|
| Zdroj: |
Proceedings of ICE: Water Management; Aug2009, Vol. 162 Issue 4, p179-188, 10p, 4 Black and White Photographs, 6 Charts, 10 Graphs |
| Abstrakt: |
In this study, applicability of feed-forward and radial-basis neural networks for monthly water consumption prediction from several socio-economic and climatic factors affecting water use is investigated. A data set including a total of 108 data records is divided into two subsets: training and testing. Firstly, the models based on a single input variable are trained and tested by feed-forward and radial methods and feed-forward and radial performances of the models are compared. Then, the models based on multiple input variables are constructed according to performances of the models based on a single input variable. The performances of feed-forward and radial models in training and testing phases are compared with the observations and the best-fit model is identified. For this purpose, several criteria such as normalised root mean square error, efficiency and correlation coefficient are calculated for all models. Subsequently, the best-fit models are also trained and tested by multiple linear regression for comparison. The results indicated that feed-forward and radial methods can be applied successfully for monthly water consumption prediction. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
