Flood Forecasting in River System Using ANFIS
- Dept. of Civil Eng., NIT, Silchar (India)
The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.
- OSTI ID:
- 21428710
- Journal Information:
- AIP Conference Proceedings, Vol. 1298, Issue 1; Conference: ICMOS 20110: International conference on modeling, optimization and computing, West Bengal (India), 28-30 Oct 2010; Other Information: DOI: 10.1063/1.3516407; (c) 2010 American Institute of Physics; ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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