Importance of parameter selection in classiffication systems using neural networks

  1. J. 1
  2. F. 2
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Aldizkaria:
Computer Aided Chemical Engineering

ISSN: 1570-7946

Argitalpen urtea: 2000

Alea: 8

Zenbakia: C

Orrialdeak: 139-144

Mota: Artikulua

DOI: 10.1016/S1570-7946(00)80025-5 SCOPUS: 2-s2.0-77956958815 GOOGLE SCHOLAR

Beste argitalpen batzuk: Computer Aided Chemical Engineering

Laburpena

In this contribution we will try to set some "general" guidelines to select the criteria (and best suited parameters) based on many test raised on an industrial example, which is a heating regulation taking place without feedback in a power plant owned by a medium size electrical company located in the north of Spain. Also we will tray to analyze from an experimental point of view the ability of NN technology for modeling the process considering a low percentage of total patterns for training, just as a measure of its tolerance to the noise. © 2000 Elsevier B.V. All rights reserved.