| Autor: |
Antonis Sentas, Lina Karamoutsou, Nikos Charizopoulos, Thomas Psilovikos, Aris Psilovikos, Athanasios Loukas |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Proceedings, Vol 2, Iss 11, p 634 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2504-3900 |
| DOI: |
10.3390/proceedings2110634 |
| Popis: |
The scope of this paper is to evaluate the short-term predictive capacity of the stochastic models ARIMA, Transfer Function (TF) and Artificial Neural Networks for water parameters, specifically for 1, 2 and 3 steps forward (m = 1, 2 and 3). The comparison of statistical parameters indicated that ARIMA models could be proposed as short-term prediction models. In some cases that TF models resulted in better predictions, the difference with ARIMA was minimal and since the latter are simpler in their construction, they are proposed for short-term prediction. Artificial Neural Networks didn’t show a good short-term predictive capacity in comparison with the aforementioned models. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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