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文章基本信息

  • 标题:Digital Ecosystem Situational Control Based on a Predictive Model
  • 本地全文:下载
  • 作者:N. Bakhtadze ; D. Elpashev ; A. Suleykin
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:1
  • 页码:300-306
  • DOI:10.1016/j.ifacol.2021.08.035
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractAn approach to the development of a digital ecosystem (DES) using predictive model and data fusion technics is presented with reference to industrial systems. Predictive models are based on data mining algorithms, wavelet analysis and the creation of knowledge bases. Digital identification models are presented, developed as digital twins for the state of DES. In turn, the control of DES is considered as situational control. The modern approach to the development of architecture for DES is proposed.
  • 关键词:Keywordsdigital ecosystemintelligent predictive modelsdata miningwavelet analysisknowledge base
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