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Water 2015, 7(6), 2707-2727; doi:10.3390/w7062707

Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

1
Department of Railroad and Civil Engineering, Dongyang University, Yeongju 750-711, Korea
2
Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843-2117, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Kwok-wing Chau
Received: 14 April 2015 / Accepted: 26 May 2015 / Published: 5 June 2015
(This article belongs to the Special Issue Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling)
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Abstract

The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP) representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop) and 11-3-1 (Levenberg-Marquardt) were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop) and 1-3-11 (Levenberg–Marquardt), which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts. View Full-Text
Keywords: areal rainfall; conjugate gradient; Kohonen self-organizing feature map; Levenberg-Marquardt; multilayer perceptron; quickprop; rainfall disaggregation areal rainfall; conjugate gradient; Kohonen self-organizing feature map; Levenberg-Marquardt; multilayer perceptron; quickprop; rainfall disaggregation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, S.; Singh, V.P. Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models. Water 2015, 7, 2707-2727.

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