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Optimum Reservoir Operation Using Dynamic Programming
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Book Synopsis Optimum Reservoir Operation Using Dynamic Programming by : National Institute of Hydrology
Download or read book Optimum Reservoir Operation Using Dynamic Programming written by National Institute of Hydrology and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimum Reservoir Operation Using Stochastic Dynamic Programming by : William Samuel Butcher
Download or read book Optimum Reservoir Operation Using Stochastic Dynamic Programming written by William Samuel Butcher and published by . This book was released on 1970 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Programming Based Operation of Reservoirs by : K. D. W. Nandalal
Download or read book Dynamic Programming Based Operation of Reservoirs written by K. D. W. Nandalal and published by Cambridge University Press. This book was released on 2007-05-10 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming is a method of solving multi-stage problems in which decisions at one stage become the conditions governing the succeeding stages. It can be applied to the management of water reservoirs, allowing them to be operated more efficiently. This is one of the few books dedicated solely to dynamic programming techniques used in reservoir management. It presents the applicability of these techniques and their limits on the operational analysis of reservoir systems. The dynamic programming models presented in this book have been applied to reservoir systems all over the world, helping the reader to appreciate the applicability and limits of these models. The book also includes a model for the operation of a reservoir during an emergency situation. This volume will be a valuable reference to researchers in hydrology, water resources and engineering, as well as professionals in reservoir management.
Book Synopsis Dynamic Programming Based Operation of Reservoirs by : K. D. W. Nandalal
Download or read book Dynamic Programming Based Operation of Reservoirs written by K. D. W. Nandalal and published by Cambridge University Press. This book was released on 2013-03-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming is a method of solving multi-stage problems in which decisions at one stage become the conditions governing the succeeding stages. It can be applied to the management of water reservoirs, allowing them to be operated more efficiently. This is one of the few books dedicated solely to dynamic programming techniques used in reservoir management. It presents the applicability of these techniques and their limits on the operational analysis of reservoir systems. The dynamic programming models presented in this book have been applied to reservoir systems all over the world, helping the reader to appreciate the applicability and limits of these models. The book also includes a model for the operation of a reservoir during an emergency situation. This volume will be a valuable reference to researchers in hydrology, water resources and engineering, as well as professionals in reservoir management.
Book Synopsis Nested algorithms for optimal reservoir operation and their embedding in a decision support platform by : Blagoj Delipetrev
Download or read book Nested algorithms for optimal reservoir operation and their embedding in a decision support platform written by Blagoj Delipetrev and published by CRC Press. This book was released on 2020-04-30 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation, named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO) variants, correspondingly MOnDP, MOnSDP and MOnRL. The idea is to include a nested optimization algorithm into each state transition, which reduces the initial problem dimension and alleviates the curse of dimensionality. These algorithms can solve multi-objective optimization problems, without significantly increasing the algorithm complexity or the computational expenses. It can additionally handle dense and irregular variable discretization. All algorithms are coded in Java and were tested on the case study of the Knezevo reservoir in the Republic of Macedonia. Nested optimization algorithms are embedded in a cloud application platform for water resources modeling and optimization. The platform is available 24/7, accessible from everywhere, scalable, distributed, interoperable, and it creates a real-time multiuser collaboration platform. This thesis contributes with new and more powerful algorithms for an optimal reservoir operation and cloud application platform. All source codes are available for public use and can be used by researchers and practitioners to further advance the mentioned areas.
Book Synopsis Improved Stochastic Dynamic Programming for Optimal Reservoir Operation Based on the Asymptotic Convergence of Benefit Differences by : Alberto Guitron de los Reyes
Download or read book Improved Stochastic Dynamic Programming for Optimal Reservoir Operation Based on the Asymptotic Convergence of Benefit Differences written by Alberto Guitron de los Reyes and published by . This book was released on 1974 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Reservoir Operation by : Geoffrey G. O'Loughlin
Download or read book Optimal Reservoir Operation written by Geoffrey G. O'Loughlin and published by . This book was released on 1971 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Stochastic Dynamic Programming Model for Optimum Operation of a Multipurpose Reservoir by : Mohammad Torabi
Download or read book A Stochastic Dynamic Programming Model for Optimum Operation of a Multipurpose Reservoir written by Mohammad Torabi and published by . This book was released on 1970 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimum Firm Power Output from a Two Reservoir System by Incremental Dynamic Programming by : Warren A. Hall
Download or read book Optimum Firm Power Output from a Two Reservoir System by Incremental Dynamic Programming written by Warren A. Hall and published by . This book was released on 1969 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis State of the Art Review by : William W-G. Yeh
Download or read book State of the Art Review written by William W-G. Yeh and published by . This book was released on 1982 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Use of Stochastic Dynamic Programming for Optimum Reservoir Management by : Thanos Trezos
Download or read book Use of Stochastic Dynamic Programming for Optimum Reservoir Management written by Thanos Trezos and published by . This book was released on 1986 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Operation of a Multiple Reservoir System by : Miguel A. Marino
Download or read book Optimal Operation of a Multiple Reservoir System written by Miguel A. Marino and published by . This book was released on 1983 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Programming Based Operation of Reservoirs by : K. D. W. Nandalal
Download or read book Dynamic Programming Based Operation of Reservoirs written by K. D. W. Nandalal and published by . This book was released on 2007 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming techniques in reservoir management for researchers and professionals in hydrology and water resources.
Book Synopsis Study of a Real-time Adaptive Closed-loop Control Algorithm for Reservoir Operation by : Ross B. Buchanan
Download or read book Study of a Real-time Adaptive Closed-loop Control Algorithm for Reservoir Operation written by Ross B. Buchanan and published by . This book was released on 1981 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Hydrologic Models and Their Representation in Stochastic Dynamic Programming Algorithms for Reservoir Operation Optimization by : Paolo Henrique Siqueira Born
Download or read book Hydrologic Models and Their Representation in Stochastic Dynamic Programming Algorithms for Reservoir Operation Optimization written by Paolo Henrique Siqueira Born and published by . This book was released on 1988 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Optimization Analysis in Hydrosystem Engineering by : Ehsan Goodarzi
Download or read book Introduction to Optimization Analysis in Hydrosystem Engineering written by Ehsan Goodarzi and published by Springer Science & Business Media. This book was released on 2014-02-06 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basics of linear and nonlinear optimization analysis for both single and multi-objective problems in hydrosystem engineering. The book includes several examples with various levels of complexity in different fields of water resources engineering. The examples are solved step by step to assist the reader and to make it easier to understand the concepts. In addition, the latest tools and methods are presented to help students, researchers, engineers and water managers to properly conceptualize and formulate resource allocation problems, and to deal with the complexity of constraints in water demand and available supplies in an appropriate way.
Book Synopsis Reinforcement Learning and Dynamic Programming Using Function Approximators by : Lucian Busoniu
Download or read book Reinforcement Learning and Dynamic Programming Using Function Approximators written by Lucian Busoniu and published by CRC Press. This book was released on 2017-07-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.