𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Rainfall-runoff model usingan artificial neural network approach

✍ Scribed by S. Riad; J. Mania; L. Bouchaou; Y. Najjar


Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
490 KB
Volume
40
Category
Article
ISSN
0895-7177

No coin nor oath required. For personal study only.


📜 SIMILAR VOLUMES


Rainfall-runoff modelling using artifici
✍ A. R. Senthil Kumar; K. P. Sudheer; S. K. Jain; P. K. Agarwal 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 206 KB

## Abstract Growing interest in the use of artificial neural networks (ANNs) in rainfall‐runoff modelling has suggested certain issues that are still not addressed properly. One such concern is the use of network type, as theoretical studies on a multi‐layer perceptron (MLP) with a sigmoid transfer

Integrating hydrometeorological informat
✍ Yen-Ming Chiang; Fi-John Chang 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 213 KB

The major purpose of this study is to effectively construct artificial neural networks-based multistep ahead flood forecasting by using hydrometeorological and numerical weather prediction (NWP) information. To achieve this goal, we first compare three mean areal precipitation forecasts: radar/NWP m

Rainfall-runoff models using artificial
✍ Dae-Il Jeong; Young-Oh Kim 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 865 KB

## Abstract Previous ensemble streamflow prediction (ESP) studies in Korea reported that modelling error significantly affects the accuracy of the ESP probabilistic winter and spring (i.e. dry season) forecasts, and thus suggested that improving the existing rainfall‐runoff model, TANK, would be cr

Identification of physical processes inh
✍ Ashu Jain; K. P. Sudheer; Sanaga Srinivasulu 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 286 KB

## Abstract The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes

A data-driven algorithm for constructing
✍ K. P. Sudheer; A. K. Gosain; K. S. Ramasastri 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 104 KB

## Abstract A new approach for designing the network structure in an artificial neural network (ANN)‐based rainfall‐runoff model is presented. The method utilizes the statistical properties such as cross‐, auto‐ and partial‐auto‐correlation of the data series in identifying a unique input vector th