caa a22 4500 605469180 CHVBK 20210128100321.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00500-014-1290-0 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1290-0 de Jesús Rubio José Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, Col. Santa Catarina, 02250, Mexico, D.F., Mexico aut Analytic neural network model of a wind turbine [Elektronische Daten] [José de Jesús Rubio] In this paper, an analytic neural network model is introduced for the modeling of the wind turbine behavior. The proposed hybrid method is the combination of the analytic and neural network models. The neural network model is used as a compensator to improve the approximation of the analytic model. It is guaranteed that the error of the analytic neural network model is smaller than the error of the analytic model. Two experiments show the effectiveness of the proposed technique. Springer-Verlag Berlin Heidelberg, 2014 Neural network modeling nationallicence Analytic modeling nationallicence Wind turbine nationallicence Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3455-3463 1432-7643 19:12<3455 2015 19 500 https://doi.org/10.1007/s00500-014-1290-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1290-0 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- de Jesús Rubio José Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, Col. Santa Catarina, 02250, Mexico, D.F., Mexico aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3455-3463 1432-7643 19:12<3455 2015 19 500