Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study
In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is th...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2006-01-01
|
| Series: | Nonlinear Processes in Geophysics |
| Online Access: | http://www.nonlin-processes-geophys.net/13/443/2006/npg-13-443-2006.pdf |
| id |
doaj-31e4ef86b6d44ecf99185ba739f827c2 |
|---|---|
| record_format |
Article |
| spelling |
doaj-31e4ef86b6d44ecf99185ba739f827c22020-11-24T22:45:50ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462006-01-01134443448Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative studyA. PiotrowskiJ. J. NapiórkowskiP.M. RowińskiIn this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is the best model for 3- and 6-h lead time prediction and the only reliable one for 9-h lead time forecasting for the largest flood used as a test case.http://www.nonlin-processes-geophys.net/13/443/2006/npg-13-443-2006.pdf |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
A. Piotrowski J. J. Napiórkowski P.M. Rowiński |
| spellingShingle |
A. Piotrowski J. J. Napiórkowski P.M. Rowiński Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study Nonlinear Processes in Geophysics |
| author_facet |
A. Piotrowski J. J. Napiórkowski P.M. Rowiński |
| author_sort |
A. Piotrowski |
| title |
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| title_short |
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| title_full |
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| title_fullStr |
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| title_full_unstemmed |
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| title_sort |
flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study |
| publisher |
Copernicus Publications |
| series |
Nonlinear Processes in Geophysics |
| issn |
1023-5809 1607-7946 |
| publishDate |
2006-01-01 |
| description |
In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is the best model for 3- and 6-h lead time prediction and the only reliable one for 9-h lead time forecasting for the largest flood used as a test case. |
| url |
http://www.nonlin-processes-geophys.net/13/443/2006/npg-13-443-2006.pdf |
| work_keys_str_mv |
AT apiotrowski flashfloodforecastingbymeansofneuralnetworksandnearestneighbourapproachndashacomparativestudy AT jjnapiorkowski flashfloodforecastingbymeansofneuralnetworksandnearestneighbourapproachndashacomparativestudy AT pmrowiampx0144ski flashfloodforecastingbymeansofneuralnetworksandnearestneighbourapproachndashacomparativestudy |
| _version_ |
1725687268660740096 |