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Introduction To Water Resources Systems - University Of Colorado Boulder, Joseph Kasprzyk
Introduction To Water Resources Systems - University Of Colorado Boulder, Joseph Kasprzyk
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This is the introductory lecture to a Water Resource Systems and Management class from Spring 2017 at the University of Colorado Boulder, by Joseph Kasprzyk. Learning goals include (i) defining integrated water resources management, (ii) identifying Colorado water management issues (ii) identifying how RiverWare simulation and optimization can be used to develop water plans (iii) use the HyMod model to perform rainfall-runoff modeling (iv) generating random parameter samples and understanding how parameter uncertainty affects model results.
Engineering Optimization: Methods/Applications - Colorado State University, John Labadie
Engineering Optimization: Methods/Applications - Colorado State University, John Labadie
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This course provides a comprehensive treatment of methods of optimization with focus on linear programming and its extensions, network flow optimization, integer programming, quadratic programming, and an introduction to nonlinear programming. The goal is to maintain a balance between theory, numerical computation, problem setup for solution by computer algorithms, and engineering applications. Course taught at Colorado State University.
Environmental Systems Analysis - Hong Kong University Of Science And Technology, Hong Kong, Ng Tze Ling
Environmental Systems Analysis - Hong Kong University Of Science And Technology, Hong Kong, Ng Tze Ling
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Undergraduate course in environmental systems analysis offered at Hong Kong University of Science and Technology, Hong Kong in Fall 2015.
Water Resources Systems Analysis - University Of Texas San Antonio, Marcio Giacomoni
Water Resources Systems Analysis - University Of Texas San Antonio, Marcio Giacomoni
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Systems Analysis methods use algorithmic and mathematical approaches for problem-solving. These are powerful methods that can be applied to solve complex design and management problems for water resources systems and other engineering areas. This class will focus on optimization methods, such as linear programming, integer programming, nonlinear programming, genetic algorithms, and dynamic programming, and their application to water resources systems. Advanced Systems Analysis methods, including sensitivity analysis, alternatives generation, and multi-objective optimization will be introduced to address the complexities associated with public sector decision-making. Course taught at University of Texas San Antonio.
Water Resources Systems Analysis - Colorado State University, Darrell Fontane
Water Resources Systems Analysis - Colorado State University, Darrell Fontane
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Applications of systems analysis, simulation and optimization techniques in water resources planning and management. Course taught at Colorado State University.
Environmental Systems Modeling And Management - University Of Virginia, Charlottesville, Teresa Culver
Environmental Systems Modeling And Management - University Of Virginia, Charlottesville, Teresa Culver
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Grad/Undergrad course in environmental systems modeling and management offered at University of Virginia, Charlottesville in Fall 2013.
Deterministic Optimization And Design - University Of California, Davis, Jay R. Lund
Deterministic Optimization And Design - University Of California, Davis, Jay R. Lund
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Undergraduate course in deterministic optimization and design offered at U.C. Davis.
Water Resources Systems Analysis - Course Notes, A Bruce Bishop, Trevor Hughes, Mac Mckee
Water Resources Systems Analysis - Course Notes, A Bruce Bishop, Trevor Hughes, Mac Mckee
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Water resources systems analysis course notes for CEE 6410 taught at Utah State University. Coverage includes:
Chapter 1 - Concepts and methods
Chapter 2 - Linear programming-introduction and graphical methods
Chapter 3 - Linear programming - simplex method
Chapter 4 - Linear programming - applications to simple water problems
Chapter 5 - Dual LP and post optimality analysis
Chapter 6 - Integer programming
Chapter 7 - More applications of integer programmign
Chapter 8 - Piecewise linearization
Chapter 9 - Other types of LP models
Chapter 10 - Dynamic programming
Chapter 11 - Gradient-based nonlinear optimization methods
Chapter 12 - Genetic …