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Computational intelligence framework for context-aware decision making
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-1938-0985
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Haugesund University College, Haugesund, Norway.
2017 (English)In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no Supp. 4, p. 2146-2157Article in journal (Refereed) Published
Abstract [en]

Learning of context-aware systems is necessary in building up knowledge on the characteristics of the environment to provide efficient decision making within multi-objective requirements. As the industrial systems becomes complex day-by-day, intelligent machine learning techniques need to be implemented at respective context-aware situations to facilitate recommendations using soft computing methods based on dynamic user specifications. In this paper, a framework is designed for a meta-database that is generated by contextual information of several peers with what-if conditions and rule-based approaches and thus by provide decision making utilizing several existing soft computing algorithms.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 8, no Supp. 4, p. 2146-2157
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-12534DOI: 10.1007/s13198-014-0320-8Local ID: bb19a94c-2a20-4100-9168-55e7b1d8deadOAI: oai:DiVA.org:ltu-12534DiVA, id: diva2:985485
Note

Validerad;2017;Nivå 2;2017-11-27 (rokbeg)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-27Bibliographically approved

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Thaduri, AdithyaKumar, Uday

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