Parameter Estimation in a Three-Dimensional Wind Field Model Using Genetic Algorithms

Authors:
Eduardo Rodríguez;Gustavo Montero;Rafael Montenegro;José María Escobar;José María González-Yuste
Affiliations:
-;-;-;-;-
Venue:
ICCS '02 Proceedings of the International Conference on Computational Science-Part I
Year:
2002

Citing 5
Cited 4

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
A parallel genetic algorithm for the set partitioning problem

A parallel genetic algorithm for the set partitioning problem
Tetrahedral Mesh Generation for Environmental Problems over Complex Terrains

ICCS '02 Proceedings of the International Conference on Computational Science-Part I
The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best

Proceedings of the 3rd International Conference on Genetic Algorithms
Uniform Crossover in Genetic Algorithms

Proceedings of the 3rd International Conference on Genetic Algorithms

Parameter estimation in a 3-D wind field adaptive model using GAs

ICECT'03 Proceedings of the third international conference on Engineering computational technology
Genetic algorithms for an improved parameter estimation with local refinement of tetrahedral meshes in a wind model

Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
Improved objective functions for tetrahedral mesh optimisation

ICCS'03 Proceedings of the 1st international conference on Computational science: PartI
Updating incomplete factorization preconditioners for shifted linear systems arising in a wind model

Journal of Computational and Applied Mathematics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The efficiency of a mass consistent model for wind field adjustment depends on several parameters that arise in various stages of the process. First, those involved in the construction of the initial wind field using horizontal interpolation and vertical extrapolation of the wind measures registered at meteorological stations. On the other hand, the Gauss precision moduli which allow from a strictly horizontal wind adjustment to a pure vertical one. In general, the values of all of these parameters are based on empirical laws. The main goal of this work is the estimation of these parameters using genetic algorithms, such that the wind velocities observed at the measurement station are regenerated as much as possible by the model.