Neuro-dynamic programming for the efficient management of reservoir networks
AbstractThe management of a water reservoir can be improved thanks to the use of stochastic dynamic programming (SDP) to generate management policies which are efficient with respect to the management objectives (flood protection, water supply for irrigation and hydropower generation, respect of minimum environmental flows, etc.). The improvement in efficiency is even more remarkable when the problem involves a reservoir network, that is a set of reservoirs which are interconnected. Unfortunately, SDP is affected by the “curse of dimensionality” and computing time and computer memory occupation can quickly become unbearable. Neuro-dynamic programming (NDP) can sensibly reduce the demands on computer time and memory thanks to the approximation of Bellman functions with Artificial Neural Networks (ANNs). In this paper an application of neuro-dynamic programming to the problem of the management of reservoir networks is presented.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 42233.
Date of creation: Dec 2001
Date of revision:
Water reservoir management; Stochastic dynamic programming; Neuro-dynamic programming;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- O13 - Economic Development, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
- P28 - Economic Systems - - Socialist Systems and Transition Economies - - - Natural Resources; Environment
- Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
- Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
- N5 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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- de Rigo, Daniele, 2013.
"Software uncertainty in integrated environmental modelling: the role of semantics and open science,"
44201, University Library of Munich, Germany.
- de Rigo, Daniele, 2013. "Software uncertainty in integrated environmental modelling: the role of semantics and open science," MPRA Paper 45960, University Library of Munich, Germany.
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