Entropy in design phase: A higraph-based model approach

Hycham Aboutaleb, Bruno Monsuez

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

Abstract

The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a methodology, a framework and a environment to handle the system model complexity. For that, it is necessary to be able to measure the system model entropy. This paper highlights the requirements a model needs to fulfill to match human user expectations. It suggests a hierarchical graphbased formalism for modeling complex systems and presents transformations to handle the underlying complexity. Finally, a way to measure system model structural complexity based on Shannon theory of information is proposed.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Information Reuse and Integration, IRI 2017
EditorsLatifur Khan, Balaji Palanisamy, Chengcui Zhang, Sahra Sedigh Sarvestani
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages526-534
Number of pages9
ISBN (Electronic)9781538615621
DOIs
Publication statusPublished - 8 Nov 2017
Event18th IEEE International Conference on Information Reuse and Integration, IRI 2017 - San Diego, United States
Duration: 4 Aug 20176 Aug 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Information Reuse and Integration, IRI 2017
Volume2017-January

Conference

Conference18th IEEE International Conference on Information Reuse and Integration, IRI 2017
Country/TerritoryUnited States
CitySan Diego
Period4/08/176/08/17

Keywords

  • Complexity
  • Entropy
  • Higraph
  • Information theory
  • Metrics
  • System modeling

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