A study of the importance of occupancy to building cooling load in prediction by intelligent approach-Reference-Cited by-同舟云学术

A study of the importance of occupancy to building cooling load in prediction by intelligent approach

Published:2011-07 Issue:7 Volume:52 Page:2555-2564
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Kwok Simon S.K.,Lee Eric W.M.

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference41 articles.

1. Degelman LO. A model for simulation of daylighting and occupancy sensors as an energy control strategy for office buildings. In: Proceedings of building simulation, vol. 99, Kyoto, Japan; 1999.

2. Mahdavi A, Proglhof C. User behavior and energy performance in buildings. IEWT; 2009.

3. A generalized stochastic model for simulation of occupant presence;Page;Energy Build,2008

4. Robinson D. Some trends and research needs in energy and comfort prediction. Comfort and energy use in buildings, Windsor, United Kingdom; 2006.

5. Page J, Robinson D, Scartezzini JL. Stochastic simulation of occupant presence and behaviour in buildings. In: Proceedings: building simulation; 2007.

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