Journal ArticleDOI
Multireservoir Modeling with Dynamic Programming and Neural Networks
TLDR
The multireservoir model based on the dynamic programming-neural network algorithm gives improved performance in this study.Abstract:
For optimal multireservoir operation, a dynamic programming-based neural network model is developed in this study. In the suggested model, multireservoir operating rules are derived using a feedforward neural network from the results of three state variables' dynamic programming algorithm. The training of the neural network is done using a supervised learning approach with the back-propagation algorithm. A multireservoir system called the Parambikulam Aliyar Project system is used for this study. The performance of the new multireservoir model is compared with (1) the regression-based approach used for deriving the multireservoir operating rules from optimization results; and (2) the single-reservoir dynamic programming-neural network model approach. The multireservoir model based on the dynamic programming-neural network algorithm gives improved performance in this study.read more
Citations
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Journal ArticleDOI
An adaptive learning framework for forecasting seasonal water allocations in irrigated catchments
TL;DR: All four developed ANN models demonstrated ANN capability of forecasting end-of-season water allocation provided sufficient data on historic allocation are available, and SOI incorporated ANN model was the most promising forecasting tool that showed good performance during the field testing.
DissertationDOI
Design of optimal reservoir operating rules in large water resources systems combining stochastic programming, fuzzy logic and expert criteria
TL;DR: A methodological framework and the required tools to improve the operation of large-scale water resource systems and has been applied to the Jucar river system (Eastern Spain), in which scarce resources are allocated following complex decision-making processes.
Journal ArticleDOI
Evolving neural networks and fuzzy clustering for multireservoir operations
A. Moradi,Alireza B. Dariane +1 more
TL;DR: Improvement of ENN when applied for parallel-series reservoirs, further improvement via fuzzy clustering, and third, development of an allocation technique for reservoirs with parallel and cascade configuration are developed.
Journal ArticleDOI
An optimisation model for reservoir operation
TL;DR: In this article, a methodology for determining reservoir operating rules in a multi-reservoir water system using a linear programming model is presented, which includes optimisation and simulation tools within an implicit stochastic optimisation framework.
DissertationDOI
Exploring data mining for hydrological modelling
TL;DR: In this article, the authors present a completely novel data mining algorithm, called AMCA, able to automatically identify the most suitable model configurations for a given catchment, using minimum data requirements and an inventory of model structures.
References
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Journal ArticleDOI
Reservoir Management and Operations Models: A State‐of‐the‐Art Review
TL;DR: The objective of this paper is to review the state-of-the-art of mathematical models developed for reservoir operations, including simulation, which include linear programming, dynamic programming, nonliner programming, and simulation.
Journal ArticleDOI
Rainfall forecasting in space and time using a neural network
TL;DR: A neural network is developed to forecast rainfall intensity fields in space and time using a three-layer learning network with input, hidden, and output layers and is shown to perform well when a relatively large number of hidden nodes are utilized.
Journal ArticleDOI
Dynamic programming applications in water resources
TL;DR: In this paper, the authors present a survey of dynamic programming models for water resource problems and examine computational techniques which have been used to obtain solutions to these problems, including aqueduct design, irrigation system control, project development, water quality maintenance, and reservoir operations analysis.
Journal ArticleDOI
Reservoir‐System Simulation and Optimization Models
TL;DR: A broad array of computer models have been developed for evaluating reservoir operations as discussed by the authors, and selecting a modeling and analysis approach for a particular application depends upon the characteristics of the reservoir characteristics.
Journal ArticleDOI
Neural-Network Models of Rainfall-Runoff Process
Jason Smith,Robert N. Eli +1 more
TL;DR: In this article, a back-propagation neural network is trained to predict the peak discharge and the time of peak resulting from a single rainfall pattern, and the neural network was trained to map a time series of three rainfall patterns into a continuum of discharges over future time by using a discrete Fourier series fit to the runoff hydrograph.