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Ergebnisse nach Hochschule und Institut

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Invasive weed optimization for solving index tracking problems
(Springer, 2015) Affolter, Konstantin; Hanne, Thomas; Schweizer, Daniel; Dornberger, Rolf
01A - Beitrag in wissenschaftlicher Zeitschrift
Using consumer behavior data to reduce energy consumption in smart homes
(2015) Schweizer, Daniel; Zehnder, Michael; Wache, Holger; Zanatta, Danilo; Rodriguez, Miguel; Witschel, Hans Friedrich
This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life smart home event data. The performance of the proposed algorithm is compared to existing algorithms regarding completeness/correctness of the results, run times as well as memory consumption and elaborates on the shortcomings of the different solutions.
04B - Beitrag Konferenzschrift
Index Tracking with Invasive Weed Optimization
(27.09.2014) Affolter, Konstantin; Dornberger, Rolf; Hanne, Thomas; Schweizer, Daniel
06 - Präsentation