Modeling Occupancy Behavior for Energy Efficiency and Occupants Comfort Management in Intelligent Buildings
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- @InProceedings{Yu:2010:ICMLA,
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author = "Tina Yu",
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title = "Modeling Occupancy Behavior for Energy Efficiency and
Occupants Comfort Management in Intelligent Buildings",
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booktitle = "Ninth International Conference on Machine Learning and
Applications (ICMLA 2010)",
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year = "2010",
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month = "12-14 " # dec,
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pages = "726--731",
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address = "Washington, DC, USA",
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isbn13 = "978-1-4244-9211-4",
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keywords = "genetic algorithms, genetic programming, energy
efficiency, intelligent buildings, motion sensor data,
occupancy behaviour modelling, occupants comfort
management, building management systems, energy
conservation",
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URL = "http://www.cs.mun.ca/~tinayu/Publications_files/PID1505499.pdf",
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DOI = "doi:10.1109/ICMLA.2010.111",
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abstract = "We applied genetic programming algorithm to learn the
behaviour of an occupant in single person office based
on motion sensor data. The learnt rules predict the
presence and absence of the occupant with
80percent-83percent accuracy on testing data from 5
different offices. The rules indicate that the
following variables may influence occupancy behaviour:
1) the day of week, 2) the time of day, 3) the length
of time the occupant spent in the previous state, 4)
the length of time the occupant spent in the state
prior to the previous state, 5) the length of time the
occupant has been in the office since the first arrival
of the day. We evaluate the rules with various
statistics, which confirm some of the previous findings
by other researchers. We also provide new insights
about occupancy behaviour of these offices that have
not been reported previously.",
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notes = "Dept. of Comput. Sci., Memorial Univ. of Newfoundland,
St. John's, NL, Canada. Also known as \cite{5708933}",
- }
Genetic Programming entries for
Tina Yu
Citations