Rainfall-Runoff Modeling Using Artificial Neural Network
DOI:
https://doi.org/10.11113/mjce.v13.15640Keywords:
Artificial Neural Network, MLP, RBF, Rainfall-Runoff ModellingAbstract
The Artificial Neural Network (ANN) is a method of computation inspired by
studies of the brain and nervous systems in biological organisms. A neural
network method is considered as a robust tools for modelling many of complex
non-linear hydrologic processes. It is a flexible mathematical structure which is
capable of modelling the rainfall-runoff relationship due to its ability to
generalize patterns in imprecise or ‘noisy’ and ambiguous input and output data
sets. This paper describes the application of multilayer perceptron (MLP) and
radial basis function (RBF) to predict daily runoff as a function of daily rainfall
for the Sungai Lui, Sungai Klang, Sungai Bekok, Sungai Slim and Sungai Ketil
catchments area. The performance of ANN is evaluated based on the efficiency
and the error. It has been found that the ANN has a potential for successful
application to the problem of runoff prediction.
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