We present a micro-prediction approach to predict individual passenger's destination station and arrival time. As a global apriori model we empirically learn a ...
ABSTRACT. Metro transport plays a large role in major cities around the world as an easily accessible and convenient means of transit. We propose.
A novel approach to forecast the metro network flow of passengers, which is exceptionally useful for city planning, is proposed and can be successfully ...
We present a micro-prediction approach to predict individual passenger's destination station and arrival time. As a global apriori model we empirically learn a ...
Apr 25, 2024 · https://dblp.org/rec/conf/gis/LinPZ17 · Eric Lin, Jinhyung D. Park, Andreas Züfle: Real-Time Bayesian Micro-Analysis for Metro Traffic ...
A Bayesian spatial–temporal model for predicting passengers ...
www.sciencedirect.com › article › pii
This work builds a Bayesian spatial–temporal model for predicting station occupancy. The proposed one provides point estimations of daily passenger flow.
We extracted three weeks of passenger flow to carry out multistep prediction tests and a comparison analysis. The results indicate that the proposed SSA-AWELM ...
People also ask
Which algorithm used in traffic prediction?
How machine learning is used in traffic prediction?
Aug 11, 2017 · We present a triple layer micro-prediction approach to predict a passenger's destination time and a station. The first layer develops a ...
This paper proposes a novel metro-net oriented method, called the probability tree based passenger flow model, which is also based on historic origin- ...
Nov 3, 2023 · Accurate and reliable real-time metro passenger flow data is indispensable for developing effective traffic plans, which is crucial for managing ...