Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Visual Analytics for Informed Decisions
Jönköping University, School of Engineering, JTH. Research area Information Engineering. (JTH. Forskningsmiljö Informationsteknik, JTH. Research area Information Engineering, Model Driven System Realisation)
Jönköping University, School of Engineering, JTH. Research area Information Engineering.
Jönköping University, School of Engineering, JTH. Research area Information Engineering. (Information Engineering)ORCID iD: 0000-0002-5881-0669
2013 (English)Conference paper, Poster (Refereed)
Abstract [en]

Energy efficiency heavily depends on effective building construction. It is more appropriate if one can predict energy efficiency of the house before building it.Here simple application of the Nearest Neighbors lazy learning techniques improveestimating the energy efficiency of a building. Visual analytics tools considered a smart solution as a function of modeling parameters by using Machine Learning framework in a suitable way. It is a powerful way to improve energy saving in building construction and making informed decisions.“LIONsolver with a novel implementation of machine learning plus optimization provides a highly advanced environment for predictive analytics. In this poster a case study from the LIONbook is presented where the energy consumption for a newhouse project is predicted. The predictive analytics environment of LIONsolver in this case study has transformed the optimal design from a very complicated and time consuming process to a very speedy and simple strategy for design and decisionmaking.”

Place, publisher, year, edition, pages
Sapienza, 2013.
Keyword [en]
Decision Making, Integrated optimization, Machine learning, Optimization tool
National Category
Communication Systems Interaction Technologies Computer and Information Science
Identifiers
URN: urn:nbn:se:hj:diva-23116OAI: oai:DiVA.org:hj-23116DiVA: diva2:687755
Conference
The International CAE Conference, October 21-22 2013, Verona, Italy
Available from: 2014-01-15 Created: 2014-01-15 Last updated: 2015-11-09Bibliographically approved

Open Access in DiVA

No full text

Other links

http://www.caeconference.com/poster/pdf/07_Vaezipour_Seigerroth_Mosavi.pdf

Search in DiVA

By author/editor
Seigerroth, Ulf
By organisation
JTH. Research area Information EngineeringJTH. Research area Information Engineering
Communication SystemsInteraction TechnologiesComputer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

Total: 277 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf