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City Transit Ridership Forecasting Based on Weather Conditions-Case Study of the Chicago Transit Authority (CTA)

机译:基于天气条件的城市公交乘客预测-以芝加哥公交管理局(CTA)为例

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摘要

Chicago Transit Authority (CTA) total ridership data is analysis considering weather data of the weekday. The results that lower temperature influences the transit ridership a lot and the influence reduces when the mean temperature goes higher are discovered. Different weather factors are analyzed to see how they affect the total ridership. In addition, a logistical regression model is generated based on the January 2014's weekday data.
机译:芝加哥运输管理局(CTA)的总乘客量数据是在考虑周日天气数据的情况下进行分析的。发现较低的温度对过境乘车的影响很大,而当平均温度升高时,影响减小。分析了不同的天气因素,以了解它们如何影响总的乘车率。此外,基于2014年1月的工作日数据生成了逻辑回归模型。

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