Role of hidden neurons in a RBF type ANN in stream flow forecasting
Loading...
Supplementary material
Other Title
Authors
Fernando, Achela
Shamseldin, Asaad
Shamseldin, Asaad
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2007-12
Supervisors
Type
Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
Artificial Neural Network (ANN)
radial basis functions
baseflow
interflow
surface runoff
radial basis functions
baseflow
interflow
surface runoff
ANZSRC Field of Research Code (2020)
Citation
Fernando, A., & Shamseldin, A. (2007). Role of hidden neurons in a RBF type ANN in stream flow forecasting. In L. Oxley, & D. Kulasiri, (Eds.). MODSIM 2007 International Congress on Modelling and Simulation. (pp. 2306-2311). Available from http://www.mssanz.org.au/MODSIM07/papers/42_s3/RoleOfHidden_s3A_Fernando_.pdf
Abstract
Although the use of Artificial Neural Networks (ANNs) in hydrological forecasting is widespread, the use of ANNs is occasionally treated with some scepticism due to its “Black Box” nature. Their use has posed some discomfort among some of the users of traditional models in that there is no explanation of the underlying actual hydrometeorological processes that contribute to the modelled phenomena.
This paper intends to present the outcome of a study conducted using the data of a stream in New Zealand to illustrate that the hidden neurons in an ANN modelling tool, indeed, do have roles to play in representing the various processes involved in the hydrological phenomenon. It sheds light on the role of the hidden neurons in a Radial Basis Function (RBF) type ANN used to forecast the streamflows using the antecedent daily flow data.
It is shown that (a) the modeller can determine the level to which the hydrograph is decomposed and, therefore, the complexity of the neural network, (b) each node in the hidden layer of neurons plays a role in reconstructing the hydrograph from its components, and that (c) the contributions from the hidden layer neurons are representative of the components that make up the flow hydrograph both quantitatively and qualitatively.
It is suggested that further numerical experiments with varying catchment characteristics be carried out to make conclusive remarks regarding the shapes of the composition hydrographs and ascertain if they mimic any of the traditional flow separation techniques.
Publisher
978-0-9758400-4-7
Permanent link
Link to ePress publication
DOI
Copyright holder
Authors
Copyright notice
All rights reserved