Development of an occupancy prediction model using indoor environmental data based on machine learning techniques-Reference-Cited by-同舟云学术

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Development of an occupancy prediction model using indoor environmental data based on machine learning techniques

Published:2016-10 Issue: Volume:107 Page:1-9
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Ryu Seung Ho,Moon Hyeun Jun

Funder

Korea government Ministry of Knowledge Economy

Ministry of Land, Infrastructure and Transport of Korean government

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference23 articles.

1. A generalised stochastic model for the simulation of occupant presence;Page;Energy Build.,2007

2. A generalized probabilistic formula relating occupant behavior to environmental conditions;Wang;Build. Environ.,2016

3. An ontology to represent energy-related occupant behavior in buildings. Part I: introduction to the DNAs framework;Hong;Build. Environ.,2015

4. Simulating the human-building interaction: development and validation of an agent-based model of office occupant behaviors;Langevin;Build. Environ.,2015

5. Does the occupant behavior match the energy concept of the building?–Analysis of a German naturally ventilated office building;Schakib-Ekbatan;Build. Environ.,2015

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