Partially connected neural networks for mapping problems

Sanggil Kang, Can Isik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, we use partially connected feed-forward neural networks (PCFNNs) for input-output mapping problems to avoid a difficulty in determining epoch while fully connected feed-forward neural networks (FCFNNs) are being trained. PCFNNs can also, in some cases, improve generalization. Our method can be applicable to real input-output mapping problems such as blood pressure estimation and etc.

Original languageEnglish (US)
Title of host publicationICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems
EditorsSlimane Hammoudi, Joaquim Filipe, Olivier Camp, Mario Piattini
PublisherEscola Superior de Tecnologia do Instituto Politecnico de Setubal
Pages469-473
Number of pages5
ISBN (Electronic)9729881618
StatePublished - Jan 1 2003
Event5th International Conference on Enterprise Information Systems, ICEIS 2003 - Angers, France
Duration: Apr 23 2003Apr 26 2003

Publication series

NameICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems
Volume2

Other

Other5th International Conference on Enterprise Information Systems, ICEIS 2003
CountryFrance
CityAngers
Period4/23/034/26/03

Keywords

  • Coupled input
  • Generalization
  • Input type
  • Partially connected feed-forward neural network
  • Uncoupled input

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Kang, S., & Isik, C. (2003). Partially connected neural networks for mapping problems. In S. Hammoudi, J. Filipe, O. Camp, & M. Piattini (Eds.), ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems (pp. 469-473). (ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems; Vol. 2). Escola Superior de Tecnologia do Instituto Politecnico de Setubal.