- Tytuł:
- Real-time forecasting of water levels using adaptive neuro- fuzzy systems
- Autorzy:
-
Gautam, D. K.
Holz, K. P.
Meyer, Z. - Powiązania:
- https://bibliotekanauki.pl/articles/241104.pdf
- Data publikacji:
- 2001
- Wydawca:
- Polska Akademia Nauk. Instytut Budownictwa Wodnego PAN
- Tematy:
-
real-time forecasting
high water levels
adaptive
neuro-fuzzy systems
Odra River - Opis:
- Real-time forecasting of high water levels at the mouth section of the Odra river is important for the safety conditions of shipping, shipyard works, river banks pro-tection, flood control and overall management of aquatic environment in the area. While numerical hydrodynamic models offer one possible solution, such models require forecasting of all boundary conditions and forcing data, calibration of model parameters and are often too complex and time consuming. These models are not very suitable for real-time forecasting where fast solutions are required to provide ad-equate lead time. Simpler approaches offered by artificial intelligence methods such as artificial neural networks and fuzzy rule-based systems are thus becoming more attractive and promising alternatives. These methods provide a fast, sufficiently good and low-cost solution. In this paper, an application of Adaptive-Network-Based Fuzzy Inference System (ANFIS) is presented for real-time forecasting of water levels at Police on the mouth section of the Odra river.
- Źródło:
-
Archives of Hydro-Engineering and Environmental Mechanics; 2001, 48, 4; 3-21
1231-3726 - Pojawia się w:
- Archives of Hydro-Engineering and Environmental Mechanics
- Dostawca treści:
- Biblioteka Nauki
Artykuł