Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Joan Ferré-Giné"'
Autor:
L. Amat, Ramon Carbó-Dorca, Xavier Gironés, Yoram Cohen, Alex Arenas, Gabriela Espinosa, Joan Ferré-Giné, Francesc Giralt
Publikováno v:
AIChE Journal. 50:1315-1343
A new approach is presented for the development of quantitative structure–property relations (QSPR) based on the extraction of relevant molecular features with self-organizing maps and the use of a modified fuzzy-ARTMAP classifier for variable pred
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c119e888d303e3d9f103b03b6011f53
https://doi.org/10.1002/aic.10116
https://doi.org/10.1002/aic.10116
Publikováno v:
Computers & Chemical Engineering. 26:1735-1754
A predictive Fuzzy ARTMAP neural system and two hybrid networks, each combining a dynamic unsupervised classifier with a different kind of supervised mechanism, were applied to develop virtual sensor systems capable of inferring the properties of man
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e7c0b3f58a6fea0392f559004de8f45
https://doi.org/10.1016/s0098-1354(02)00148-5
https://doi.org/10.1016/s0098-1354(02)00148-5
Publikováno v:
Physics of Fluids. 12:1826-1835
An artificial neural network, based on fuzzy ARTMAP, that is capable of learning the basic nonlinear dynamics of a turbulent velocity field is presented. The neural system is capable of generating a detailed multipoint time record with the same struc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acc95e6d0ab6310a8ebada65d0527441
https://doi.org/10.1063/1.870430
https://doi.org/10.1063/1.870430
Publikováno v:
Scopus-Elsevier
An automatic procedure based on of the Fuzzy ARTMAP neural network is applied to classify the structure embedded in two-component velocity signals measured in a turbulent wake behind a circular cylinder. A small part of the velocity field in the hori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90bd4a5fb7339132c569c30dbf9e9fe4
https://doi.org/10.1016/s0954-1810(97)00003-4
https://doi.org/10.1016/s0954-1810(97)00003-4