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Machine learning integrated optimization for decision making
Jönköping University, School of Engineering, JTH. Research area Information Engineering.
Jönköping University, School of Engineering, JTH. Research area Information Engineering.
Jönköping University, School of Engineering, JTH. Research area Information Engineering.ORCID iD: 0000-0002-5881-0669
2013 (English)In: EURO|INFORMS 26TH EUROPEAN CONFERENCE ON OPERATIONAL RESEARCH MMXIIIRoME, 2013Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Due to the dynamic nature of stored big data in today’s political and behavioral decision-making, inter-temporal choice and marketing, enterprise decision management, etc., the traditional approaches of statistical analysis, analytics, information processing and business intelligence have become less useful in making the informed decisions. Here, the novel methodology of integration of data mining, modeling, and interactive decision-making is studied as an effective approach where numerous what-if scenarios are evaluated and optimizationbased decision processes are used.

Place, publisher, year, edition, pages
2013.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hj:diva-23124OAI: oai:DiVA.org:hj-23124DiVA, id: diva2:687849
Conference
The 26th EURO-INFORMS Conference, July 1-4 2013, Rome, Italy
Available from: 2014-01-15 Created: 2014-01-15 Last updated: 2015-11-09

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http://euro2013.org/wp-content/uploads/program-euro26.pdf

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Seigerroth, Ulf

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