Improving Low-Cost Sail Simulator Results by Artificial Neural Networks Models View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009-09-30

AUTHORS

V. Díaz Casás , P. Porca Belío , F. López Peña , R. J. Duro

ABSTRACT

In the present study a method is proposed to reduce the error level of these simplified simulators by correcting the results achieved by means of neural network based approximations. The results of simple aerodynamic simulators used within an evolutionary sail design process are used as application example. The neural network correction is carried out in this case by comparing the numerical results with wind tunnel experiments performed on sail models. More... »

PAGES

139-149

Book

TITLE

Advances in Machine Learning and Data Analysis

ISBN

978-90-481-3176-1
978-90-481-3177-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-90-481-3177-8_9

DOI

http://dx.doi.org/10.1007/978-90-481-3177-8_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045704303


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