A computer-aided visualization tool for stochastic theory education in water resources engineering

2009 ◽  
Vol 17 (4) ◽  
pp. 398-411 ◽  
Author(s):  
Jonathan Schwenk ◽  
Faisal Hossain ◽  
David Huddleston
Keyword(s):  
Water Resources ◽  
Stochastic Theory ◽  
Visualization Tool ◽  
Computer Aided ◽  
Water Resources Engineering

Use of Multiobjective Evolutionary Algorithms in Water Resources Engineering

2010 ◽  
pp. 45-82 ◽  
Author(s):  
Francisco Venícius Fernandes Barros ◽  
Eduardo Sávio Passos Rodrigues Martins ◽  
Luiz Sérgio Vasconcelos Nascimento ◽  
Dirceu Silveira Reis
Keyword(s):  
Water Resources ◽  
Evolutionary Algorithms ◽  
Multiobjective Evolutionary Algorithms ◽  
Water Resources Engineering

Development of a Digital Image CD-ROM and Website: A New Resource for Water Resources Engineering Education

2003 ◽  
Author(s):  
John W. Nicklow ◽  
Lizette R. Chevalier ◽  
Bill T. Ray ◽  
Lilly A. Boruszkowski
Keyword(s):  
Water Resources ◽  
Engineering Education ◽  
Digital Image ◽  
Cd Rom ◽  
Water Resources Engineering

Water Resources Engineering

2021 ◽  
pp. 279-334
Author(s):  
P.K. Jayasree ◽  
K Balan ◽  
V Rani
Keyword(s):  
Water Resources ◽  
Water Resources Engineering

scholarly journals Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review

2020 ◽  
Vol 3 (1) ◽  
pp. 135-188 ◽  
Author(s):  
M. Janga Reddy ◽  
D. Nagesh Kumar
Keyword(s):  
Water Resources ◽  
Evolutionary Algorithms ◽  
Swarm Intelligence ◽  
Water Resource ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
State Of The Art ◽  
Real Life ◽  
Distribution Networks ◽  
Water Resources Engineering

Abstract During the last three decades, the water resources engineering field has received a tremendous increase in the development and use of meta-heuristic algorithms like evolutionary algorithms (EA) and swarm intelligence (SI) algorithms for solving various kinds of optimization problems. The efficient design and operation of water resource systems is a challenging task and requires solutions through optimization. Further, real-life water resource management problems may involve several complexities like nonconvex, nonlinear and discontinuous functions, discrete variables, a large number of equality and inequality constraints, and often associated with multi-modal solutions. The objective function is not known analytically, and the conventional methods may face difficulties in finding optimal solutions. The issues lead to the development of various types of heuristic and meta-heuristic algorithms, which proved to be flexible and potential tools for solving several complex water resources problems. This paper provides a review of state-of-the-art methods and their use in planning and management of hydrological and water resources systems. It includes a brief overview of EAs (genetic algorithms, differential evolution, evolutionary strategies, etc.) and SI algorithms (particle swarm optimization, ant colony optimization, etc.), and applications in the areas of water distribution networks, water supply, and wastewater systems, reservoir operation and irrigation systems, watershed management, parameter estimation of hydrological models, urban drainage and sewer networks, and groundwater systems monitoring network design and groundwater remediation. This paper also provides insights, challenges, and need for algorithmic improvements and opportunities for future applications in the water resources field, in the face of rising problem complexities and uncertainties.

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