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Occupancy

About: Occupancy is a research topic. Over the lifetime, 2757 publications have been published within this topic receiving 68288 citations.


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Journal ArticleDOI
TL;DR: In this paper, the authors examined the effects of stochastically generated occupancy schedules on the energy performance of a multiresidential high-rise building located in Shanghai, China and found that occupant behavior affects cooling more than heating.

28 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used various statistical methods, such as correlation analysis, decision tree, and Mann-Whitney U test, based on the actual occupancy data from public office buildings in South Korea.

28 citations

Journal ArticleDOI
TL;DR: This paper proposes to use low invasive, fast-sampling infrared array sensors to collect data from the actual scene and establish the Inhomogeneous Hidden Markov Model to capture the time dependence of occupancy for buildings occupancy estimation.
Abstract: Along with methods such as Hidden Markov Model and Linear Discriminant Analysis, environmental sensors including temperature, humidity or carbon dioxide are used to estimate indoor occupancy, which have various applications. Most of the previous studies have neglected the time-dependent character of the indoor occupancy information or real-time response of the system. In this paper, we propose to use low invasive, fast-sampling infrared array sensors to collect data from the actual scene and establish the Inhomogeneous Hidden Markov Model to capture the time dependence of occupancy for buildings occupancy estimation. First, to avoid raw sensor datas susceptibility to external influences, the non-negative matrix factorization is adopted to reduce the dimension of the raw matrix and eliminate interferences caused by environmental changes. Second, the Softmax Regression Model is used to calculate the emission probability matrix for clarifying the dynamic relationship between environmental parameters and indoor occupancy, which is weak. Third, the Forward algorithm and the Viterbi algorithm are applied to achieve online and off-line estimation. Experiments are made with real recorded data. Our performance results demonstrate that method we proposed is effective for indoor occupancy estimation.

28 citations

Journal ArticleDOI
TL;DR: It is suggested that linear features that affect patch size may be more important than point features in determining sagebrush-obligate songbird occupancy when compared to structural effects such as habitat fragmentation and increased predation.
Abstract: Development associated with natural gas extraction may have negative effects on wildlife. Here we assessed the effects of natural gas development on the distributions of three sagebrush-obligate birds (Brewer's Sparrow, Spizella breweri; Sagebrush Sparrow, Amphispiza belli; and Sage Thrasher, Oreoscoptes montanus) at a natural gas extraction site in Wyoming, USA. Two drivers of habitat disturbance were investigated: natural gas well pads and roadways. Disturbances were quantified on a small scale (minimum distance to a disturbance) and a large scale (landscape density of a disturbance). Their effects on the study species' distributions were assessed using a multi-scale occupancy model. Minimum distances to wells and roadways were found to not have significant impacts on small-scale occupancy. However, roadway and well density at the landscape-scale significantly impacted the large-scale occupancy of Sagebrush Sparrows and Sage Thrashers. The results confirmed our hypotheses that increasing road density negatively affects the landscape-scale occupancy rates of Sagebrush Sparrow and Sage Thrasher, but did not confirm our hypothesis that increasing well density would negatively impact large-scale occupancy. We therefore suggest that linear features that affect patch size may be more important than point features in determining sagebrush-obligate songbird occupancy when compared to structural effects such as habitat fragmentation and increased predation. We recommend that future well construction be focused along existing roadways, that horizontal drilling be used to reduce the need for additional roads, and that deactivation and restoration of roadways be implemented upon the deactivation of wells, we also recommend a possible mitigation strategy when new roads are to be built.

28 citations

Journal ArticleDOI
TL;DR: It is identified that the statistical methods have rarely been applied to model the electric demand, power factor, or domestic water use, and the use of an occupancy variable and novel model forms are also areas with limited literature.
Abstract: A significant portion of energy consumption occurs in buildings today. Accurate and easy-to-implement methods are needed to calculate building energy consumption for a wide range of applications. These areas have attracted research interest as early as the 1980's. Among a number of approaches for building energy analysis, the statistical methods have remained popular because they are simple to use and able to provide accurate prediction of building energy consumption. As the availability and quality of building energy data continue to improve, the methodologies behind building energy calculation also evolved over time. Although relevant areas such as calibrated simulation and machine learning methods have had numerous recent literature reviews, the statistical methods have not been reviewed in depth. This work aims to fill this knowledge gap for whole-building energy consumption modelling. This work will discuss how the methodology developed through time and summarise the applications of this approach in various areas of building energy analysis. This work has identified that the statistical methods have rarely been applied to model the electric demand, power factor, or domestic water use. The use of an occupancy variable and novel model forms are also areas with limited literature.

28 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023669
20221,420
2021234
2020217
2019236
2018209