caa a22 4500 445874635 CHVBK 20180317145524.0 cr unu---uuuuu 170323e20110601xx s 000 0 eng 10.1007/s10652-010-9175-y doi (NATIONALLICENCE)springer-10.1007/s10652-010-9175-y Sahay Rajeev Department of Civil Engineering, Birla Institute of Technology, 835215, Mesra, Ranchi, India aut Prediction of longitudinal dispersion coefficients in natural rivers using artificial neural network [Elektronische Daten] [Rajeev Sahay] An artificial neural network (ANN) model is developed for predicting the longitudinal dispersion coefficient in natural rivers. The model uses few rivers' hydraulic and geometric characteristics, that are readily available, as the model input, and the target output is the longitudinal dispersion coefficient (K). For performance evaluation of the model, using published field data, predictions by the developed ANN model are compared with those of other reported important models. Based on various performance indices, it is concluded that the new model predicts the longitudinal dispersion coefficient more accurately. Sensitive analysis performed on input parameters indicates stream width, flow depth, stream sinuosity, flow velocity, and shear velocity to be the most influencing parameters for accurate prediction of the longitudinal dispersion coefficient. Springer Science+Business Media B.V., 2010 Dispersion nationallicence Longitudinal dispersion coefficient nationallicence Artificial neural network nationallicence Streams nationallicence Pollutant dispersion nationallicence River flow nationallicence Environmental Fluid Mechanics Springer Netherlands 11/3(2011-06-01), 247-261 1567-7419 11:3<247 2011 11 10652 https://doi.org/10.1007/s10652-010-9175-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10652-010-9175-y text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Sahay Rajeev Department of Civil Engineering, Birla Institute of Technology, 835215, Mesra, Ranchi, India aut NATIONALLICENCE 773 0- Environmental Fluid Mechanics Springer Netherlands 11/3(2011-06-01), 247-261 1567-7419 11:3<247 2011 11 10652 Metadata rights reserved Springer special CC-BY-NC licence nationallicence SWISSBIB 196111188 BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer