Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/78679
Author(s): J. Nuno Fidalgo
Rui Camacho
António F. Silva
Fernando Aristides
Title: Machine learning methods to predict wind intensity
Issue Date: 2008
Abstract: A decision making problem often becomes a problem of selection. In this kind of problems (decision making or fo-recasting problems) the selection of an effective set of input variables, which is usually a complex and sometimes an unmanageable process, is the main problem in real situations. The correct selection of the most important data in the assessment of a problem allows not only faster decision but the reduction of the prediction error. In this paper we use a hybrid model of a Genetic Algorithm as a heuristic tool, to select appropriate combinations of different variables that have more effect on forecasting decision making parameters, and Artificial Neural Network as a fitness function of genetic algorithm. The model was then applied to predict the intensity of the wind in the short and medium term in the central-south region of Portugal. The results proved to be excellent regardless of the forecast horizon.
Subject: Outras ciências da engenharia e tecnologias
Other engineering and technologies
Scientific areas: Ciências da engenharia e tecnologias::Outras ciências da engenharia e tecnologias
Engineering and technology::Other engineering and technologies
URI: https://repositorio-aberto.up.pt/handle/10216/78679
Source: Proceedings of the WSEAS International Conference on APPLIED and THEORETICAL MECHANICS
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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