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Weather-Driven Insights: Predicting Household Electricity Usage with AI
Khawaja, Taimoor
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2024 (English)
Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE credits
Student thesis
Place, publisher, year, edition, pages
2024.
National Category
Computer and Information Sciences
Identifiers
URN:
urn:nbn:se:ltu:diva-110447
OAI: oai:DiVA.org:ltu-110447
DiVA, id:
diva2:1906868
Educational program
Master Programme in Data Science
Supervisors
Gupta, Payal, Biträdande universitetslektor
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
Examiners
Elragal, Ahmed, Professor
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
Available from:
2024-10-21
Created:
2024-10-20
Last updated:
2025-10-21
Bibliographically approved
Open Access in DiVA
fulltext
(3119 kB)
150 downloads
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FULLTEXT01.pdf
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3119 kB
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cdcfdd26bf7d70de17f60e3c24655aa290be87713f7a7d346033fef84a2ce64b7c30adcde94763d460f13292ad443173c3442e81888f5f05433a4165cc5be58f
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fulltext
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Khawaja, Taimoor
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Total: 151 downloads
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Direct link
https://ltu.diva-portal.org/smash/record.jsf?pid=diva2:1906868
Cite
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apa
ieee
modern-language-association-8th-edition
vancouver
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apa
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
de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
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html
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