Modeling Occupancy Behavior for Energy Efficiency and Occupants Comfort Management in Intelligent Buildings

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Yu:2010:ICMLA,
  author =       "Tina Yu",
  title =        "Modeling Occupancy Behavior for Energy Efficiency and
                 Occupants Comfort Management in Intelligent Buildings",
  booktitle =    "Ninth International Conference on Machine Learning and
                 Applications (ICMLA 2010)",
  year =         "2010",
  month =        "12-14 " # dec,
  pages =        "726--731",
  address =      "Washington, DC, USA",
  isbn13 =       "978-1-4244-9211-4",
  keywords =     "genetic algorithms, genetic programming, energy
                 efficiency, intelligent buildings, motion sensor data,
                 occupancy behaviour modelling, occupants comfort
                 management, building management systems, energy
                 conservation",
  URL =          "http://www.cs.mun.ca/~tinayu/Publications_files/PID1505499.pdf",
  DOI =          "doi:10.1109/ICMLA.2010.111",
  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.",
  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