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- W2016185718 abstract "Based on the analysis of existing mobile phone positioning and detection methods, a dynamic distribution model has been proposed to detect urban population density based on the phone location data using an improved K-means clustering algorithm. The purpose of this real-time model analysis is to first detect the density and flow characteristics of urban population mobility according to the phone location data and then to dynamically monitor the real-time state and density of road traffic and urban population with low cost, all-weather detection capability and so on. The experimental study shows that better results can be achieved using our improved K-means clustering algorithm. We believe that such a model is helpful to the automatic detection of population density and road traffic." @default.
- W2016185718 created "2016-06-24" @default.
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- W2016185718 date "2010-06-01" @default.
- W2016185718 modified "2023-09-27" @default.
- W2016185718 title "A dynamic model for urban population density estimation using mobile phone location data" @default.
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- W2016185718 doi "https://doi.org/10.1109/iciea.2010.5514844" @default.
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