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- W4317418513 abstract "The purpose of this paper is to investigate the factors affecting the passenger traffic volume on the high-capacity MRT, to analyze the traffic volume trends, and to make traffic volume predictions more accurately. This paper uses the LSTM (Long Short-term Memory) model and regression analysis for Taipei MRT passenger traffic volume prediction. The training data, including dates, temperatures and number of passengers, were collected, and a regression analysis was performed to find trends in the data." @default.
- W4317418513 created "2023-01-19" @default.
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- W4317418513 date "2022-10-18" @default.
- W4317418513 modified "2023-09-26" @default.
- W4317418513 title "Using LSTM and Regression Analysis for Railway Passenger Traffic Volume Prediction" @default.
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- W4317418513 doi "https://doi.org/10.1109/gcce56475.2022.10014238" @default.
- W4317418513 hasPublicationYear "2022" @default.
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