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The Use of Stochastic Models for Short-Term Prediction of Water Parameters of the Thesaurus Dam, River Nestos, Greece
- Source :
- Proceedings, Vol 2, Iss 11, p 634 (2018)
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 25043900
- Volume :
- 2
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Proceedings
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.54d978f7819543c88669539f4afcb624
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/proceedings2110634