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An analyze of long-term hourly district heat demand forecasting of a commercial building using neural networks
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. (EST)
2016 (English)In: The 8th International Conference on Applied Energy – ICAE2016, 2016Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
2016.
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Energy Systems
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URN: urn:nbn:se:mdh:diva-34708OAI: oai:DiVA.org:mdh-34708DiVA, id: diva2:1068136
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The 8th International Conference on Applied Energy – ICAE2016
Available from: 2017-01-24 Created: 2017-01-24 Last updated: 2017-01-24Bibliographically approved

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Maher, Azaza

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CiteExportLink to record
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  • de-DE
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