A PCA-BPN approach for estimating simulation workload in cloud manufacturing

Tin-Chih Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Cloud manufacturing is a novel manufacturing technology that supports factories distributed around the world with ubiquitous accesses to manufacturing resources. Estimating the simulation workload for simulating a factory online is an important topic to cloud manufacturing. To investigate this, a principal component analysis (PCA)-back propagation network (BPN) approach is proposed in this study. The real data of some simulation tasks have been collected to test the proposed methodology. The experimental results supported the superiority of the proposed methodology over some existing methods in terms of the estimation accuracy.

Original languageEnglish
Title of host publicationICUFN 2015 - 7th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages826-830
Number of pages5
ISBN (Electronic)9781479989935
DOIs
StatePublished - 7 Aug 2015
Event7th International Conference on Ubiquitous and Future Networks, ICUFN 2015 - Sapporo, Japan
Duration: 7 Jul 201510 Jul 2015

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2015-August
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Conference

Conference7th International Conference on Ubiquitous and Future Networks, ICUFN 2015
CountryJapan
CitySapporo
Period7/07/1510/07/15

Keywords

  • back propagation network
  • Cloud manufacturing
  • estimation
  • principal component analysis
  • simulation workload
  • ubiquitous

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