Process Identification through modular neural networks and rule extraction

B J vanderZwaag, C H Slump, Lambert Spaanenburg

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

Sammanfattning

Monolithic neural networks may be trained from measured data to establish knowledge
about the process. Unfortunately, this knowledge is not guaranteed to be found
and – if at all – hard to extract. Modular neural networks are better suited for this
purpose. Domain-ordered by topology, rule extraction is performed module by module.
This has all the benefits of a divide-and-conquer method and opens the way to
structured design. This paper discusses a next step in this direction by illustrating the
potential of base functions to design the neural model.
Originalspråkengelska
Titel på värdpublikationProceedings of the Fourteenth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'02)
Sidor507-508
StatusPublished - 2002
Externt publiceradJa
EvenemangBelgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2002 - Leuven, Belgien
Varaktighet: 2002 okt. 212002 okt. 22

Publikationsserier

Namn
ISSN (tryckt)1568-7805

Konferens

KonferensBelgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2002
Land/TerritoriumBelgien
OrtLeuven
Period2002/10/212002/10/22

Ämnesklassifikation (UKÄ)

  • Elektroteknik och elektronik

Fingeravtryck

Utforska forskningsämnen för ”Process Identification through modular neural networks and rule extraction”. Tillsammans bildar de ett unikt fingeravtryck.

Citera det här