Data-driven Modelling in River Channel Evolution Rese Artificial Neural Networks Applications

Year 2015, Volume: 10 Issue: 4, 384 - 398, 30.10.2015

Z. Rozlach

Abstract

Any interaction with river systems requires detailed consideration of channel evolution.  The  multiplicity  of physical processes  occurring  within catchment  and channel-floodplain complex  causes complicated processes in river channel. Therefore, it demands reliable and accurate methods in research, which are capable to  consider  exclusive and non-linear relationships  in river  system.  In the recent years, new approaches, relied on intelligence models of machine learning are proposed. Among them artificial neural networks (ANN) method is presently widely  used in the data-driven  modelling  for non-linear system  behaviour.  This paper 

presents a review of artificial neural network models and numerous applications of ANNs in river channel processes research.

Keywords

artificial neural networks, intelligence models, channel processes, sediment transport, channel erosion

References

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