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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:

FASTNN: A Deep Learning Approach for Traffic Flow Prediction Considering Spatiotemporal Features
Qianqian Zhou, Nan Chen, Siwei Lin
Sensors (2022) Vol. 22, Iss. 18, pp. 6921-6921
Open Access | Times Cited: 23

Showing 23 citing articles:

Connecting the indispensable roles of IoT and artificial intelligence in smart cities: A survey
Hoang Nguyen, Dina Nawara, Rasha Kashef
Journal of Information and Intelligence (2024)
Open Access | Times Cited: 23
Challenges and opportunities in traffic flow prediction: review of machine learning and deep learning perspectives
Syed Aleem Uddin Gilani, Murad Al-Rajab, Mahmoud Bakka
Data & Metadata (2024) Vol. 3, pp. 378-378
Closed Access | Times Cited: 20
Deep learning solutions for smart city challenges in urban development
Pengjun Wu, Zhanzhi Zhang, Xueyi Peng, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Enhancement of traffic forecasting through graph neural network-based information fusion techniques
Shams Forruque Ahmed, Sweety Angela Kuldeep, Sabiha Jannat Rafa, et al.
Information Fusion (2024) Vol. 110, pp. 102466-102466
Open Access | Times Cited: 10
Graph Neural Networks and Open-Government Data to Forecast Traffic Flow
Petros Brimos, Areti Karamanou, Evangelos Kalampokis, et al.
Information (2023) Vol. 14, Iss. 4, pp. 228-228
Open Access | Times Cited: 16
Addressing imbalance in graph datasets: Introducing GATE-GNN with graph ensemble weight attention and transfer learning for enhanced node classification
Abdul Joseph Fofanah, David Chen, Lian Wen, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124602-124602
Open Access | Times Cited: 5
Nonlinear Prediction Model of Vehicle Network Traffic Management Based on the Internet of Things
Zhong Peng, Lili Yin
Systems and Soft Computing (2025), pp. 200254-200254
Open Access
Convolutional Long-Short Term Memory Network with Multi-Head Attention Mechanism for Traffic Flow Prediction
Yupeng Wei, Hongrui Liu
Sensors (2022) Vol. 22, Iss. 20, pp. 7994-7994
Open Access | Times Cited: 18
Incorporating Multivariate Auxiliary Information for Traffic Prediction on Highways
Bao Li, Jing Xiong, Feng Wan, et al.
Sensors (2023) Vol. 23, Iss. 7, pp. 3631-3631
Open Access | Times Cited: 5
Self-Supervised Spatiotemporal Masking Strategy-Based Models for Traffic Flow Forecasting
Gang Liu, Silu He, Xing Han, et al.
Symmetry (2023) Vol. 15, Iss. 11, pp. 2002-2002
Open Access | Times Cited: 4
Lag and duration of leader–follower relationships in mixed traffic using causal inference
David Demitri Africa, Ronald Benjamin Dy Quiangco, Clark Kendrick Go
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 1
Open Access | Times Cited: 1
Construction of Short-Term Traffic Flow Prediction Model Based on IoT and Deep Learning Algorithms
Xiaowei Sun, Huili Dou
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
ST-D3DDARN: Urban traffic flow prediction based on spatio-temporal decoupled 3D DenseNet with attention ResNet
Jing Chen, Yang Guowei, Zhaochong Zhang, et al.
PLoS ONE (2024) Vol. 19, Iss. 6, pp. e0305424-e0305424
Open Access | Times Cited: 1
Enhancing Urban Resilience to Flooding in Hydrogeological Risk Areas Through Big Data Analytics Using Deep Neuro-Fuzzy System
Varun Malik, John Martin, Ruchi Mittal, et al.
Research Square (Research Square) (2024)
Closed Access | Times Cited: 1
Soil Erosion Type and Risk Identification from the Perspective of Directed Weighted Complex Network
Tu Ping, Qianqian Zhou, Meng Qi
Sustainability (2023) Vol. 15, Iss. 3, pp. 1939-1939
Open Access | Times Cited: 2
Self-Constructed Deep Fuzzy Neural Network for Traffic Flow Prediction
Jiyao An, Jin Zhao, Qingqin Liu, et al.
Electronics (2023) Vol. 12, Iss. 8, pp. 1885-1885
Open Access | Times Cited: 2
Addressing Imbalance in Graph Datasets: Introducing Gate-Gnn with Graph Ensemble Weight Attention and Transfer Learning for Enhanced Node Classification
Abdul Joseph Fofanah
(2023)
Closed Access | Times Cited: 2
Staf: Convolutional Spatio-Temporal Transformer Architecture Based on Augmented Feature Learning for Traffic Flow Forecasting
Abdul Joseph Fofanah, David Chen, Lian Wen, et al.
(2024)
Closed Access
A multi-task spatio-temporal fully convolutional model incorporating interaction patterns for traffic flow prediction
Qianqian Zhou, Ping Tu, Nan Chen
International Journal of Geographical Information Science (2024), pp. 1-39
Closed Access
MSTMN: a novel meta-attention-based multi-task spatiotemporal network for traffic flow prediction
Qianqian Zhou, Nan Chen
Neural Computing and Applications (2024) Vol. 36, Iss. 36, pp. 23195-23222
Closed Access
Multi-Channel Spatio-Temporal Graph Convolutional Networks for Accurate Micromobility Demand Prediction Integrating Public Transport Data
Linda Belkessa, Mostafa Ameli, Mohsen Ramezani, et al.
(2024), pp. 5-13
Closed Access
Deep Learning's Current and Future Applications in Predicting Vehicle Traffic Flow
Yiyang Hu, He Zhang, Hongfeng Jiang
Highlights in Science Engineering and Technology (2024) Vol. 119, pp. 524-532
Closed Access
Traffic Flow Prediction with Swiss Open Data: A Deep Learning Approach
Petros Brimos, Areti Karamanou, Evangelos Kalampokis, et al.
Lecture notes in computer science (2023), pp. 313-328
Closed Access | Times Cited: 1
An Ecosystem for Deploying Artificial Intelligence in Public Administration
Areti Karamanou, Evdokia Mangou, Konstantinos Tarabanis
Lecture notes in computer science (2023), pp. 192-207
Closed Access
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