Using entropy to maximize the usefulness of data collection

  • This paper presents a generic methodology for measurement system configuration when the goal is to identify behaviour models that reasonably explain observations. For such tasks, the best measurement system provides maximum separation between candidate models. In this work, the degree of separation between models is measured using Shannon’s Entropy Function. The location and type of measurement devices are chosen such that the entropy of candidate models is greatest. This methodology is tested on a laboratory structure and, to demonstrate generality, an existing fresh water supply network in a city in Switzerland. In both cases, the methodology suggests an appropriate set of sensors for identifying the state of the system.

Download full text files

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Document Type:Conference Proceeding
Author: Yvan Robert-Nicoud, Benny Raphael, Ian F. C. Smith
DOI (Cite-Link):https://doi.org/10.25643/bauhaus-universitaet.117Cite-Link
URN (Cite-Link):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20111215-1177Cite-Link
Language:English
Date of Publication (online):2004/10/22
Year of first Publication:2004
Release Date:2004/10/22
Institutes:Fakultät Bauingenieurwesen / Professur Informatik im Bauwesen
GND Keyword:Mobile Computing; Funknetz; Entropie
Dewey Decimal Classification:600 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
BKL-Classification:54 Informatik / 54.89 Angewandte Informatik: Sonstiges
56 Bauwesen / 56.03 Methoden im Bauingenieurwesen
Collections:Bauhaus-Universität Weimar / International Conference on Computing in Civil and Building Engineering, ICCCBE, Weimar / International Conference on Computing in Civil and Building Engineering, ICCCBE, Weimar 10. 2004
Licence (German):License Logo In Copyright