Short-term Passenger Flow Prediction Research of Urban Rail Transit under Rainfall Conditions
DOI:
https://doi.org/10.54097/ajst.v5i3.8023Keywords:
Short-term Passenger Flow Prediction, Rainfall Conditions, Cloud Model.Abstract
The short-term passenger flow prediction in urban rail transit serves as a crucial basis for dynamic adjustments of transportation organizations, enhancing the efficiency of operational services and safety assurances, while effectively advancing the development of intelligent rail transit systems. By examining the impact of adverse weather conditions on rail transit passenger flow, conducting research on cloud models, and analyzing existing short-term passenger flow prediction models, this study proposes a novel concept for a short-term dynamic passenger flow prediction model based on cloud models under rainfall conditions.
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