Vapnik's learning theory applied to energy consumption forecasts in residential buildings

DOI10.1080/00207160802033582zbMath1170.68557OpenAlexW2096096387MaRDI QIDQ3535725

Frédéric Magoulès, Fred Lherminier, Florence Lai

Publication date: 14 November 2008

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160802033582

zbMATH Keywords

energy conservationdata miningpredictive modellingstatistical learning theoryenergy efficiency

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Learning and adaptive systems in artificial intelligence (68T05) Identification in stochastic control theory (93E12) Optimal stochastic control (93E20) Stochastic learning and adaptive control (93E35) Fault detection; testing in circuits and networks (94C12)

Cites Work

• Optimal operations management and network planning of a district heating system with a combined heat and power plant
• Propositional Satisfiability Algorithm to Find Minimal Reducts for Data Mining
• Advanced Lectures on Machine Learning
• Unnamed Item

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