Sentence examples for water resource optimization from inspiring English sources
Evolutionary algorithms (EAs) have been widely used in handling various water resource optimization problems in recent years.
Results obtained offer an improved knowledge on how the control parameter values affect DEA's search behavior, thereby providing guidance for parameter-tuning and hence hopefully increasing appropriate take-up of the DEA within the industry in tackling water resource optimization problems.
A water resources optimization model is developed based on interval-parameter two-stage stochastic programming.
Over the last two decades, evolutionary algorithms (EAs) have become a popular approach for solving water resources optimization problems.
Genetic algorithms have been shown to be powerful tools for solving a wide variety of water resources optimization problems.
The web application has three web services for: (1) managing, presenting and storing of geospatial data, (2) support of water resources modeling and (3) water resources optimization.
This study presents an innovative integrated PPMGWO model of water resources optimization allocation in a transboundary river basin, which is integrated through the projection pursuit model (PPM) and Grey wolf optimization (GWO) method.
Many real water resources optimization problems involve conflicting objectives for which the main goal is to find a set of optimal solutions on, or near to the Pareto front.
It is based in the combined use of two models, a water resources optimization model and a stochastic streamflow generation model, to generate a series of results that allow evaluating the future state of the system.
Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations.
For example, in water resources management problems, optimization problems regularly consist of objective functions and constraints that rely on output from a PDE-based simulator.
