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• W4313306081 endingPage "101933" @default.
• W4313306081 startingPage "101933" @default.
• W4313306081 abstract "Accurate modeling of human time-activity trajectory is essential to support community resilience and emergency response strategies such as daily energy planning and urban seismic vulnerability assessment. However, existing modeling of time-activity trajectory is only driven by socio-demographic information with identical activity trajectories shared among the same group of people and neglects the influence of the environment. To further improve human time-activity trajectory modeling, this paper constructs community time-activity trajectory and analyzes how social-demographic and built environment influence people s activity trajectory based on Markov Chains and Dirichlet Regression. We use the New York area as a case study and gather data from American Time Use Survey, Policy Map, and the New York City Energy & Water Performance Map to evaluate the proposed method. To validate the regression model, Box s M Test and T-test are performed with 80% data training the model and the left 20% as the test sample. The modeling results align well with the actual human behavior trajectories, demonstrating the effectiveness of the proposed method. It also shows that both social-demographic and built environment factors will significantly impact a community's time-activity trajectory. Specifically, 1) Diversity and median age both have a significant influence on the proportion of time people assign to education activity. 2) Transportation condition affects people s activity trajectory in the way that longer commute time decreases the proportion of biological activity (eg. sleeping and eating) and increases people s working time. 3) Residential density affects almost all activities with a significant p-value for all biological needs, household management, working, education, and personal preference." @default.
• W4313306081 created "2023-01-06" @default.
• W4313306081 creator A5021733293 @default.
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• W4313306081 date "2023-03-01" @default.
• W4313306081 modified "2023-10-17" @default.
• W4313306081 title "Community time-activity trajectory modeling based on Markov chain simulation and Dirichlet regression" @default.
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• W4313306081 doi "https://doi.org/10.1016/j.compenvurbsys.2022.101933" @default.
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