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20 October 2022 Research on the characteristics of regular bus trips in Guangzhou under the influence of the new crown epidemic based on multivariate data fusion
Xiaoyu Li, Jing Tan, Yuejiang Su, Chang Yu
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Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124512G (2022) https://doi.org/10.1117/12.2655876
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China
Abstract
Conventional public transportation is an important part of public transportation, and it has always been the focus of urban transportation research to excavate the characteristics of public transportation and analyze residents' travel patterns. In 2020, the new crown epidemic broke out. The outbreak and continuation of the epidemic have caused shocks and challenges to conventional public transportation, and the characteristics of conventional public transportation have developed significantly. Taking Guangzhou as an example, this paper conducts bus IC card mining based on multisource data fusion, and conducts research on the characteristics of changes in Guangzhou's regular bus travel rules under the influence of the new crown epidemic. Research shows that under the continuous influence of the epidemic, the scale of bus trips has dropped significantly, the attraction of conventional buses to commuter passengers has been weakened, special groups are important users of public transport, and the ride code has become the most important payment method.
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Xiaoyu Li, Jing Tan, Yuejiang Su, and Chang Yu "Research on the characteristics of regular bus trips in Guangzhou under the influence of the new crown epidemic based on multivariate data fusion", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124512G (20 October 2022); https://doi.org/10.1117/12.2655876
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KEYWORDS
Data fusion
Analytical research
Data modeling
Mining
Data mining
Statistical analysis
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