Multi-criteria validation of artificial neural network rainfall-runoff modeling

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

Artificial Neural Network Model for Rainfall-Runoff Relationship

Conceptual models have been widely used and are considered to be the best choice for describing the runoff process in a watershed. In most cases, the solution accuracy is mainly based on the topographic and hydrologic information subject to certain requirements for model calibration. Thus, these types of model are inappropriate for watershed area with little hydrologic data. Artificial neural n...

Rainfall-runoff model usingan artificial neural network approach

Dual Artificial Neural Network for Rainfall-Runoff Forecasting

One of the principal issues related to hydrologic models for prediction of runoff is the estimation of extreme values (floods). It is well understood that unless the models capture the dynamics of rainfall-runoff process, the improvement in prediction of such extremes is far from reality. In this paper, it is proposed to develop a dual (combined and paralleled) artificial neural network (D-ANN)...

Artificial neural networks as rainfall- runoff models

A series of numerical experiments, in which flow data were generated from synthetic storm sequences routed through a conceptual hydrological model consisting of a single nonlinear reservoir, has demonstrated the closeness of fit that can be achieved to such data sets using Artificial Neural Networks (ANNs). The application of different standardization factors to both training and verification s...