Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/30537
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Variable selection procedures and efficient suboptimal mask search algorithms in fuzzy inductive reasoning |
Autor: | Mirats-Tur, Josep M. CSIC; Cellier, François E.; Huber Garrido, Rafael CSIC | Palabras clave: | Variable selection Behavioural modelling Inductive modelling Fuzzy inductive reasoning Suboptimal mask search Hill-climbing Control theory |
Fecha de publicación: | 2002 | Editor: | Taylor & Francis | Citación: | International Journal of General Systems 31(5): 469-498 (2002) | Resumen: | This paper describes two new suboptimal mask search algorithms for Fuzzy inductive reasoning (FIR), a technique for modelling dynamic systems from observations of their input/output behaviour. Inductive modelling is by its very nature an optimisation problem. Modelling large-scale systems in this fashion involves solving a high-dimensional optimisation problem, a task that invariably carries a high computational cost. Suboptimal search algorithms are therefore important. One of the two proposed algorithms is a new variant of a directed hill-climbing method. The other algorithm is a statistical technique based on spectral coherence functions. The utility of the two techniques is demonstrated by means of an industrial example. A garbage incinerator process is inductively modelled from observations of 20 variable trajectories. Both suboptimal search algorithms lead to similarly good models. Each of the algorithms carries a computational cost that is in the order of a few percent of the cost of solving the complete optimisation problem. Both algorithms can also be used to filter out variables of lesser importance, i.e. they can be used as variable selection tools. | Versión del editor: | http://dx.doi.org/10.1080/0308107021000042471 | URI: | http://hdl.handle.net/10261/30537 | DOI: | 10.1080/0308107021000042471 | ISSN: | 0308-1079 |
Aparece en las colecciones: | (IRII) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
doc1.pdf | 399,51 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
4
checked on 08-may-2024
Page view(s)
328
checked on 13-may-2024
Download(s)
276
checked on 13-may-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.