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
Improved particle swarm optimization algorithm for multi-reservoir system operation+
TL;DR: A hybrid improved particle swarm optimization (IPSO) algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems and the crossover and mutation idea inspired by the genetic algorithm (GA) is imported into the particle updating method to enhance the diversity of populations.
Journal ArticleDOI
Stochastic Fuzzy Neural Network: Case Study of Optimal Reservoir Operation
Paulo Chaves,Toshiharu Kojiri +1 more
TL;DR: A new approach for system optimization and operation, named stochastic fuzzy neural network (SFNN), which can be defined as a neuro-fuzzy system that is stochastically trained (optimized) by a GA model to represent the system operational strategy.
Journal ArticleDOI
Application of Cat Swarm Optimization Algorithm for Optimal Reservoir Operation
TL;DR: The scarcity of water resources throughout the world has caused many complexities in meeting water demands, which in turn has created a tendency toward developing more efficient and effective water management systems.
Journal ArticleDOI
Inferring efficient operating rules in multireservoir water resource systems: A review
TL;DR: This study has been partially funded by the ADAPTAMED project (RTI2018-101483-B-I00) from the Ministerio de Ciencia, Innovacion Universidades (MICINN) of Spain, and by the postdoctoral program of the Universitat Politecnica de Valencia (UPV).
Journal ArticleDOI
Predicting the impact of vegetations in open channels with different distributaries’ operations on water surface profile using artificial neural networks
TL;DR: In this paper, the authors used Artificial Neural Networks (ANN) for the development of various models to simulate the impact of different submerged weeds' densities, different flow discharges, and different distributaries operation scheduling on the water surface profile in an experimental main open channel.
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.
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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.