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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Passenger Flow Prediction of Urban Rail Transit Based on Deep Learning Methods
Zhi Xiong, Jianchun Zheng, Dunjiang Song, et al.
Smart Cities (2019) Vol. 2, Iss. 3, pp. 371-387
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow
Yuxin He, Lishuai Li, Xinting Zhu, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 10, pp. 18155-18174
Open Access | Times Cited: 59
Passenger flow forecasting approaches for urban rail transit: a survey
Qiuchi Xue, Wei Zhang, Meiling Ding, et al.
International Journal of General Systems (2023) Vol. 52, Iss. 8, pp. 919-947
Closed Access | Times Cited: 25
Multi-Step Peak Passenger Flow Prediction of Urban Rail Transit Based on Multi-Station Spatio-Temporal Feature Fusion Model
Jianan Sun, Xiaofei Ye, Xingchen Yan, et al.
Systems (2025) Vol. 13, Iss. 2, pp. 96-96
Open Access | Times Cited: 1
Explainable Artificial Intelligence for Developing Smart Cities Solutions
Dhavalkumar Thakker, Bhupesh Kumar Mishra, Amr Abdullatif, et al.
Smart Cities (2020) Vol. 3, Iss. 4, pp. 1353-1382
Open Access | Times Cited: 50
Research on speed sensor fusion of urban rail transit train speed ranging based on deep learning
Xuemei Zhan, Zhong Hua Mu, Rajeev Kumar, et al.
Nonlinear Engineering (2021) Vol. 10, Iss. 1, pp. 363-373
Open Access | Times Cited: 44
Forecasting public transit passenger demand: With neural networks using APC data
Shivaraj Halyal, Raviraj H. Mulangi, M. M. Harsha
Case Studies on Transport Policy (2022) Vol. 10, Iss. 2, pp. 965-975
Closed Access | Times Cited: 24
Multi-point short-term prediction of station passenger flow based on temporal multi-graph convolutional network
Yaguan Wang, Yong Qin, Jianyuan Guo, et al.
Physica A Statistical Mechanics and its Applications (2022) Vol. 604, pp. 127959-127959
Open Access | Times Cited: 21
Forecasting metro rail transit passenger flow with multiple-attention deep neural networks and surrounding vehicle detection devices
Jheng-Long Wu, Mingying Lu, Chia-Yun Wang
Applied Intelligence (2023) Vol. 53, Iss. 15, pp. 18531-18546
Open Access | Times Cited: 9
A Predictive Vehicle Ride Sharing Recommendation System for Smart Cities Commuting
Theodoros Anagnostopoulos
Smart Cities (2021) Vol. 4, Iss. 1, pp. 177-191
Open Access | Times Cited: 19
Forecast of Short-Term Passenger Flow in Multi-Level Rail Transit Network Based on a Multi-Task Learning Model
Fenling Feng, Zhaohui Zou, Chengguang Liu, et al.
Sustainability (2023) Vol. 15, Iss. 4, pp. 3296-3296
Open Access | Times Cited: 7
A two-layer modelling framework for predicting passenger flow on trains: A case study of London underground trains
Qian Zhang, Xiaoxiao Liu, Sarah K. Spurgeon, et al.
Transportation Research Part A Policy and Practice (2021) Vol. 151, pp. 119-139
Open Access | Times Cited: 14
RETRACTED ARTICLE: Optimal path planning and data simulation of emergency material distribution based on improved neural network algorithm
Min Chen
Soft Computing (2023) Vol. 27, Iss. 9, pp. 5995-6005
Open Access | Times Cited: 5
A Spatial-Temporal Graph Convolutional Recurrent Network for Transportation Flow Estimation
Ifigenia Drosouli, Athanasios Voulodimos, Paris Mastorocostas, et al.
Sensors (2023) Vol. 23, Iss. 17, pp. 7534-7534
Open Access | Times Cited: 5
A Novel Spatial–Temporal Deep Learning Method for Metro Flow Prediction Considering External Factors and Periodicity
Baixi Shi, Zihan Wang, Jianqiang Yan, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 1949-1949
Open Access | Times Cited: 1
Passenger Flow Prediction Method based on Hybrid Algorithm: Intelligent Transportation System
Ahmed Raza, Guangjie Liu, James Msughter Adeke, et al.
Deleted Journal (2024) Vol. 2, Iss. 1, pp. 12-20
Open Access
Long-Term Passenger Flow Forecasting for Rail Transit Based on Complex Networks and Informer
Dekui Li, Shubo Du, Yuru Hou
Sensors (2024) Vol. 24, Iss. 21, pp. 6894-6894
Open Access
Advancements in Passenger Flow Optimization in Smart Transport: A Holistic Survey
Harshit Raj, Karnal Patel, Sanjay Patidar
Lecture notes in networks and systems (2024), pp. 379-389
Closed Access
Public safety risk prediction of urban rail transit based on mathematical model and algorithm simulation
Lin Zuo
Soft Computing (2023)
Closed Access | Times Cited: 1
Multi-Point Short-Term Passenger Flow Prediction in the Station Based on Temporal Multi-Graph Convolutional Network
Yaguan Wang, Yong Qin, Jianyuan Guo, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 2
Passenger Flow Prediction based on Recurrent Neural Networks and Wavelet Transform
Jing Huang, Fubo Shao, Shuguo Yang
Journal of Physics Conference Series (2020) Vol. 1486, Iss. 2, pp. 022021-022021
Open Access | Times Cited: 2
A CPS-Enhanced Subway Operations Safety System Based on the Short-Term Prediction of the Passenger Flow
Shaobo Zhong, Zhi Xiong, Guannan Yao, et al.
Springer eBooks (2020), pp. 153-169
Closed Access | Times Cited: 2
Optimal path planning and data simulation of emergency material distribution based on improved neural network algorithm
Min Chen
Research Square (Research Square) (2023)
Open Access
A Variational Graph Convolution Network with Normalizing Flows for Passenger Flow Prediction
Siavash Farazmand, Raghav Narula, Zachary Patterson, et al.
(2023), pp. 237-242
Closed Access
A Graph Neural Network Based Learning Model for Urban Metro Flow Prediction
Ifigenia Drosouli, Athanasios Voulodimos, Paris Mastorocostas, et al.
(2023), pp. 1883-1888
Closed Access
An Integrated Framework for Mapping Nationwide Daily Temperature in China
Shaobo Zhong, Xinlan Ye, Mingxing Wang, et al.
Advances in Meteorology (2022) Vol. 2022, pp. 1-15
Open Access
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