Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river

R Tabbussum, AQ Dar - Journal of Flood Risk Management, 2020 - Wiley Online Library
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …

[PDF][PDF] Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river

R Tabbussum, AQ Dar - 2020 - academia.edu
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …

Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river

R Tabbussum, AQ Dar - Journal of Flood Risk Management, 2020 - ui.adsabs.harvard.edu
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …

Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river.

R Tabbussum, AQ Dar - Journal of Flood Risk Management, 2020 - search.ebscohost.com
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …

Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river.

R Tabbussum, AQ Dar - 2020 - cabidigitallibrary.org
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …

[引用][C] Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river

R Tabbussum, AQ Dar - 2020