River flow time series prediction with a range-dependent neural network;Prévision de séries temporelles de débits en rivière par un réseau de neurones dépendant d'echelle

Hydrological Sciences Journal

Volumn 46, Issue 5, 2001, Pages 729-745

  Hu, T S ^a   Lam, K C ^b   Ng, S T ^c  

^a WUHAN UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^c UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Artificial neural networks; Hydrological time series; Prediction; Range dependent neural network; River flow; Threshold auto regressive (TAR) model

Indexed keywords

ALGORITHMS; BACKPROPAGATION; COMPUTER SIMULATION; HYDROLOGY; NEURAL NETWORKS; PARAMETER ESTIMATION; TIME SERIES ANALYSIS;

RANGE-DEPENDENT NEURAL NETWORKS (RDNN);

STREAM FLOW;

ALGORITHM; FLOW ANALYSIS; NEURAL NETWORK; PREDICTION; RIVER CHANNEL;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; PREDICTION; RIVER FLOW; TIME SERIES;

CHINA;

EID: 0035472003     PISSN: 02626667     EISSN: None     Source Type: Journal    
DOI: 10.1080/02626660109492867     Document Type: Article

References (53)

1. Artificial neural networks in hydrology. I. Preliminary concepts
2. Artificial neural networks in hydrology. II. Hydrologic applications
3. A critique of current methods in hydrologic systems investigation
4. A comparison between neural-network forecasting techniques-case study: River flow forecasting
5. Successive linear programming at Exxon
6. Nonlinear least-absolute values and minimal model fitting
7. River flood forecasting with a neural network model
8. Neural modeling for time series: A statistical stepwise method for weight elimination
9. Daily reservoir inflow forecasting using ANNs with stopped training approach
10. An artificial neural approach to rainfall-runoff modelling
11. Improving generalization using double backpropagation
12. An empirical study of learning speed in back-propagation networks
13. Rainfall forecasting in space and time using a neural network
14. A nonlinear programming technique for the optimization of continuous processing systems
15. The meta-pi network: Building distributed knowledge representation for robust pattern recognition
16. Artificial neural network modelling of the rainfall-runoff process
17. Hydrological time series prediction using radial basis function network
18. Nonlinear runoff routing- A comparison of solution methods
19. River flow prediction using artificial neural networks: Generalization beyond the calibration range
20. Adaptive mixtures of local experts
21. Application of ANN for reservoir inflow prediction and operation
22. Nonlinear modelling of the rainfall-runoff models
23. Neural networks for river flow prediction
24. Forecasting river flow using nonlinear dynamics
25. Backpropagation in time-series forecasting
26. Robust error measure fir supervised neural network learning with outliners
27. Applying soft computing approaches to river level forecasting
28. A hybrid multi-model approach to rover level forecasting
29. River stage forecasting in Bangladesh: Neural network approach
30. Neural nets for modelling rainfall-runoff transformation
31. A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting
32. Neural networks for the prediction and forecasting of water resources variables: A review of modeling issues and applications
33. A neural network model of rainfall-runoff using radial basis function
34. Artificial neural networks as rainfall-runoff models
35. Improving the convergence of back propagation problem
36. Deriving a general operating policy for reservoir using neural networks
37. Multivariate modelling of water resources time series using artificial neural networks
38. Neural network-based modeling of the adequate chlorine dosage for drinking water disinfection
39. Chaos in rainfall
40. Learning representations by backpropagating errors
41. A nonlinear rainfall-runoff model using an artificial neural network
42. Application of a neural network technique to rainfall-runoff modelling
43. Neural network models of rainfall-runoff process
44. River stage forecasting using artificial neural networks
45. On a threshold model
46. Threshold autoregression, limit cycles and cyclical data (with discussion)
47. Predicting the future: A connectionist approach
48. Approximate confidence intervals for design floods for a single site using a neural network
49. Searching for chaotic dynamics in snowmelt runoff
50. Short term stream-flow forecasting using artificial neural network
51. Prediction of watershed runoff using Bayesian concepts and modular neural networks