Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/68762
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Type: Journal article
Title: Modelling of hydrological persistence for hidden state Markov decision processes
Author: Fisher, A.
Green, D.
Metcalfe, A.
Citation: Annals of Operations Research, 2012; 199(1):215-224
Publisher: Kluwer Academic Publishers
Issue Date: 2012
ISSN: 0254-5330
1572-9338
Statement of
Responsibility: 
Aiden Fisher, David Green, Andrew Metcalfe
Abstract: A reservoir in south east Queensland can supply irrigators, industry or domestic users. Stochastic inflow is modelled by a hidden state Markov chain, with three hidden states corresponding to prevailing climatic conditions. A stochastic dynamic program that relies on estimation of the hidden state is implemented. The optimal decisions are compared with those obtained if the hidden state Markov chain model is replaced with a model that relies on the Southern Oscillation Index to define prevailing climatic conditions.
Keywords: Hidden Markov model
Hidden state Markov decision process
Reservoir operation
Rights: © Springer Science+Business Media, LLC 2011
DOI: 10.1007/s10479-011-0992-2
Appears in Collections:Aurora harvest
Environment Institute publications
Mathematical Sciences publications

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