Statistical Characteristics of Individual and Group Mobility Patterns in Human Dynamics

碩士 === 國立高雄師範大學 === 物理學系 === 106 === In this study, we analyze the Human dynamics of Kaohsiung with the daily number of taxi passengers and daily taxi passenger loading time, and then use the Gaussian distribution function to fit the probability density distribution map. First, we analyzed the data...

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Bibliographic Details
Main Authors: CHEN, SIH-AN, 陳思安
Other Authors: Lih,Jiann-Shing
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/4t68vt
Description
Summary:碩士 === 國立高雄師範大學 === 物理學系 === 106 === In this study, we analyze the Human dynamics of Kaohsiung with the daily number of taxi passengers and daily taxi passenger loading time, and then use the Gaussian distribution function to fit the probability density distribution map. First, we analyzed the data for each month for a total of 15 months. The data was found to be very stable and the data fitting degree was quite good. Second, we classify the groups and find out that the long-term passenger loading ratio is the classification condition to effectively distinguish the ethnic groups. In the ethnic group classification, it can correspond to the distribution trend of the gas Maxwell-Boltzmann distribution curve. Finally, we analyzed the individual taxis separately from the data of 16 taxis and fitted them by the same analysis method. The individual taxi data fitting results were not as good as the data of the group taxi. The characteristics found in the data did not appear in the individual taxis, but the data of the taxis integrating 16 individuals exhibited the characteristics of the group taxi data, and the Gaussian fitting coefficient of determination reached 0.99. The Gauss distribution was distributed in the taxi data of the group, but in the individual Taxi data show a more disorderly distribution. Order distribution, However, the data of individual taxis integrated into group taxis shows a Gaussian distribution,, which proves that the relationship between the individual taxi and the group taxi is not based on the scaling law but the Central Limit Theorem. It shows once again that the taxi movement behavior has similar gas molecular movement patterns.