论文信息 - Setting Up Stage-Discharge Relations Using ANN

Setting Up Stage-Discharge Relations Using ANN

The artificial neural networks (ANNs) that try to mimic the functioning of the human brain are a powerful tool for input-output mapping. The setting up of a stage-discharge relation is an important part of the processing of streamflow data. Three-layer feedforward ANNs have been used to model river-rating curves. The results show that the ANN approach is much superior as compared to the conventional curve-fitting approach. The ANN is also able to model a loop-rating curve (hysteresis effect) very well.

Sharad K. Jain | S. Jain | D. Chalisgaonkar | D. Chalisgaonkar

[1] H. Raman,et al. Multivariate modelling of water resources time series using artificial neural networks , 1995 .

[2] Christian W. Dawson,et al. An artificial neural network approach to rainfall-runoff modelling , 1998 .

[3] B. S. Thandaveswara,et al. A non-linear rainfall–runoff model using an artificial neural network , 1999 .

[4] Witold F. Krajewski,et al. Rainfall forecasting in space and time using a neural network , 1992 .

[5] Kuolin Hsu,et al. Artificial Neural Network Modeling of the Rainfall‐Runoff Process , 1995 .

[6] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[7] Leung Tsang,et al. A Neural Network Approach to Inversion of Snow Water Equivalent from Passive Microwave Measurements , 1992 .

[8] Razi Gaskari,et al. Performance of a Virtual Runoff Hydrograph System , 1996 .

[9] Jason Smith,et al. Neural-Network Models of Rainfall-Runoff Process , 1995 .

[10] Nachimuthu Karunanithi,et al. Neural Networks for River Flow Prediction , 1994 .

[11] V. Chandramouli,et al. Deriving a General Operating Policy for Reservoirs Using Neural Network , 1996 .