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Identifying Prototype States within Hydrodynamic Model Outputs using a Self-Organising Feature Map

Citation

Williams, RN and de Souza, P and Jones, E and D'Este, C, Identifying Prototype States within Hydrodynamic Model Outputs using a Self-Organising Feature Map, Proceedings - Oceans 2012, 21-24 MAY 2012, YEOSU, KOREA EJ ISBN 978-1-4577-2090-1 (2012) [Non Refereed Conference Paper]


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DOI: doi:10.1109/OCEANS-Yeosu.2012.6263430

Abstract

The Coastal Environmental Modelling Team at CSIRO Marine and Atmospheric Research, in Hobart, Tasmania, Australia, has been modelling hydrodynamic conditions within the estuarine environment of south-eastern Tasmania for sev- eral years. Historical model output has been analysed in an effort to identify prototype hydrodynamic states (i.e., frequently encountered typical hydrodynamic situations) exhibited by the estuarine environment over that period. A competitive-learning neural network, the Self-Organizing Feature Map (SOM), was used to identify these prototype states. Once such a network has been trained, each node in its output layer represents a particular pattern in the input data and nodes representing similar patterns are located near to each other on the two-dimensional output grid, while those representing dissimilar patterns are further apart. Estimated daily average surface hydrodynamic conditions (salinity, temperature and ocean current components) within the south-east Tasmanian estuarine environment, from August 2009 to August 2010, were derived from output provided by the hydrodynamic model. The current components were then analysed using a SOM and subsequent inspection of the SOM output grid enabled a number of prototypical hydrodynamic states to be identified within the model outputs.

Item Details

Item Type:Non Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Pattern Recognition and Data Mining
Objective Division:Environment
Objective Group:Other Environment
Objective Field:Marine Oceanic Processes (excl. climate related)
Author:Williams, RN (Dr Ray Williams)
Author:de Souza, P (Professor Paulo de Souza Junior)
ID Code:78758
Year Published:2012
Deposited By:Computing and Information Systems
Deposited On:2012-07-24
Last Modified:2013-06-06
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