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- W2804226333 abstract "Significant changes in the urban built environment have occurred due to rapid urbanization and increases in the urban population. Such alterations may produce environmental health-related issues such as urban heat stress, air pollution and traffic noise. This research undertook a field study to collect data including urban design parameters, micro-environmental factors and city climatic information. This work was conducted over a two-year period on three pedestrian streets located in high-density urban areas in Beijing. These areas were selected in order to study the influences of urban street canyon texture within a particular geometric layout, wind flow corridors and variations in air temperature on pedestrian microclimatic comfort. The results will facilitate the work of urban planners by providing them with information for use in improving outdoor thermal comfort through their designs. A total of 60[Formula: see text]485 samples were organized into training, validation and test sets. We confirmed our hypothesis that internal wind speed ([Formula: see text] is attributable mainly to the urban texture coefficient ([Formula: see text], air temperature ([Formula: see text] and leading-in wind speed ([Formula: see text]. The model was tested using the test data collected onsite, which demonstrated a very accurate goodness-of-fit; the model achieved an R-squared value of 0.82, which meant that [Formula: see text] as a dependent variable was 82% correlated to the three predictors as independent variables. With this computer simulation, urban planners can now predict and visualize the impact of changes on the built environment in terms of either the direction of solar radiation received or increases in wind speed, in return for the desired thermal comfort level for residents of the neighborhood." @default.
- W2804226333 created "2018-06-01" @default.
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- W2804226333 date "2018-06-01" @default.
- W2804226333 modified "2023-09-28" @default.
- W2804226333 title "Towards Pedestrian Microclimatic Comfort: A Rapid Predication Model for Street Winds and Pedestrian Thermal Sensation" @default.
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- W2804226333 doi "https://doi.org/10.1142/s1793984418400068" @default.
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