Training and application of artificial neural networks with incomplete data

Zs J. Viharos, L. Monostori, T. Vincze

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

19 Citations (Scopus)

Abstract

The paper describes a novel approach for learning and applying artificial neural network (ANN) models based on incomplete data. A basic novelty in this approach is not to replace the missing part of incomplete data but to train and apply ANN-based models in a way that they should be able to handle such situations. The root of the idea is inherited form the authors. earlier research for finding an appropriate input-output configuration of ANN models [16]. The introduced concept shows that it is worth purposely impairing the data used for learning to prepare the ANN model for handling incomplete data efficiently. The applicability of the proposed solution is demonstrated by the results of experimental runs with both artificial and real data. New experiments refer to the modelling and monitoring of cutting processes.

Original languageEnglish
Title of host publicationDevelopments in Applied Artificial Intelligence - 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002, Proceedings
EditorsTim Hendtlass, Moonis Ali
PublisherSpringer Verlag
Pages649-659
Number of pages11
ISBN (Print)3540437819, 9783540437819
DOIs
Publication statusPublished - 2002
Event15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002 - Cairns, Australia
Duration: Jun 17 2002Jun 20 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2358
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002
CountryAustralia
CityCairns
Period6/17/026/20/02

Keywords

  • Applications to manufacturing
  • Machine learning
  • Neural networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Viharos, Z. J., Monostori, L., & Vincze, T. (2002). Training and application of artificial neural networks with incomplete data. In T. Hendtlass, & M. Ali (Eds.), Developments in Applied Artificial Intelligence - 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002, Proceedings (pp. 649-659). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2358). Springer Verlag. https://doi.org/10.1007/3-540-48035-8_63