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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:

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach
Haofan Yang, Tharam S. Dillon, Yi‐Ping Phoebe Chen
IEEE Transactions on Neural Networks and Learning Systems (2016) Vol. 28, Iss. 10, pp. 2371-2381
Closed Access | Times Cited: 249

Showing 1-25 of 249 citing articles:

A review of deep learning for renewable energy forecasting
Huaizhi Wang, Zhenxing Lei, Xian Zhang, et al.
Energy Conversion and Management (2019) Vol. 198, pp. 111799-111799
Closed Access | Times Cited: 861
A hybrid deep learning based traffic flow prediction method and its understanding
Yuankai Wu, Huachun Tan, Lingqiao Qin, et al.
Transportation Research Part C Emerging Technologies (2018) Vol. 90, pp. 166-180
Closed Access | Times Cited: 683
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
Haiyang Yu, Zhihai Wu, Shuqin Wang, et al.
Sensors (2017) Vol. 17, Iss. 7, pp. 1501-1501
Open Access | Times Cited: 548
Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
IEEE Transactions on Knowledge and Data Engineering (2020) Vol. 34, Iss. 8, pp. 3681-3700
Open Access | Times Cited: 534
LSTM-based traffic flow prediction with missing data
Yan Tian, Kaili Zhang, LI Jian-yuan, et al.
Neurocomputing (2018) Vol. 318, pp. 297-305
Closed Access | Times Cited: 435
Deep Spatial–Temporal 3D Convolutional Neural Networks for Traffic Data Forecasting
Shengnan Guo, Youfang Lin, Shijie Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2019) Vol. 20, Iss. 10, pp. 3913-3926
Closed Access | Times Cited: 351
Enhancing transportation systems via deep learning: A survey
Wang Yuan, Dongxiang Zhang, Ying Liu, et al.
Transportation Research Part C Emerging Technologies (2018) Vol. 99, pp. 144-163
Closed Access | Times Cited: 270
Spatiotemporal Traffic Flow Prediction with KNN and LSTM
Xianglong Luo, Danyang Li, Yu Yang, et al.
Journal of Advanced Transportation (2019) Vol. 2019, pp. 1-10
Open Access | Times Cited: 238
Deep learning models for traffic flow prediction in autonomous vehicles: A review, solutions, and challenges
Arzoo Miglani, Neeraj Kumar
Vehicular Communications (2019) Vol. 20, pp. 100184-100184
Closed Access | Times Cited: 232
Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
Clélia Lopez, Ludovic Leclercq, Panchamy Krishnakumari, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 229
Delay-Minimization Routing for Heterogeneous VANETs With Machine Learning Based Mobility Prediction
Yujie Tang, Nan Cheng, Wen Wu, et al.
IEEE Transactions on Vehicular Technology (2019) Vol. 68, Iss. 4, pp. 3967-3979
Closed Access | Times Cited: 180
Deep-Learning-Based Probabilistic Forecasting of Electric Vehicle Charging Load With a Novel Queuing Model
Xian Zhang, Ka Wing Chan, Hairong Li, et al.
IEEE Transactions on Cybernetics (2020) Vol. 51, Iss. 6, pp. 3157-3170
Open Access | Times Cited: 170
A Hierarchical Deep Domain Adaptation Approach for Fault Diagnosis of Power Plant Thermal System
Xiaoxia Wang, Haibo He, Lusi Li
IEEE Transactions on Industrial Informatics (2019) Vol. 15, Iss. 9, pp. 5139-5148
Closed Access | Times Cited: 151
Short-Term Prediction of Passenger Demand in Multi-Zone Level: Temporal Convolutional Neural Network With Multi-Task Learning
Kunpeng Zhang, Zijian Liu, Liang Zheng
IEEE Transactions on Intelligent Transportation Systems (2019) Vol. 21, Iss. 4, pp. 1480-1490
Closed Access | Times Cited: 149
Short-term prediction of lane-level traffic speeds: A fusion deep learning model
Yuanli Gu, Wenqi Lu, Lingqiao Qin, et al.
Transportation Research Part C Emerging Technologies (2019) Vol. 106, pp. 1-16
Closed Access | Times Cited: 149
Deep Learning Method Based on Gated Recurrent Unit and Variational Mode Decomposition for Short-Term Wind Power Interval Prediction
Ruoheng Wang, Chaoshun Li, Wenlong Fu, et al.
IEEE Transactions on Neural Networks and Learning Systems (2019) Vol. 31, Iss. 10, pp. 3814-3827
Closed Access | Times Cited: 144
Traffic flow prediction models – A review of deep learning techniques
Anirudh Ameya Kashyap, Shravan Raviraj, Ananya Devarakonda, et al.
Cogent Engineering (2021) Vol. 9, Iss. 1
Open Access | Times Cited: 109
Improved Deep Hybrid Networks for Urban Traffic Flow Prediction Using Trajectory Data
Zongtao Duan, Yun Yang, Kai Zhang, et al.
IEEE Access (2018) Vol. 6, pp. 31820-31827
Open Access | Times Cited: 139
A Survey on an Emerging Area: Deep Learning for Smart City Data
Qi Chen, Wei Wang, Fangyu Wu, et al.
IEEE Transactions on Emerging Topics in Computational Intelligence (2019) Vol. 3, Iss. 5, pp. 392-410
Closed Access | Times Cited: 133
Evaluation of deep learning in non-coding RNA classification
Noorul Amin, Annette McGrath, Yi‐Ping Phoebe Chen
Nature Machine Intelligence (2019) Vol. 1, Iss. 5, pp. 246-256
Closed Access | Times Cited: 124
An attention‐based deep learning model for traffic flow prediction using spatiotemporal features towards sustainable smart city
B Vijayalakshmi, K. Ramar, N. Z. Jhanjhi, et al.
International Journal of Communication Systems (2020) Vol. 34, Iss. 3
Closed Access | Times Cited: 114
A variational autoencoder solution for road traffic forecasting systems: Missing data imputation, dimension reduction, model selection and anomaly detection
Guillem Boquet, Antoni Morell, Javier Serrano, et al.
Transportation Research Part C Emerging Technologies (2020) Vol. 115, pp. 102622-102622
Open Access | Times Cited: 112
Survey of neural network‐based models for short‐term traffic state prediction
N. N. Loan, Neda Taherifar, Hai L. Vu
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2018) Vol. 9, Iss. 1
Open Access | Times Cited: 106
Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges
Sahil Khatri, Hrishikesh Vachhani, Shalin Shah, et al.
Peer-to-Peer Networking and Applications (2020) Vol. 14, Iss. 3, pp. 1778-1805
Closed Access | Times Cited: 104
Integrating Gray Data Preprocessor and Deep Belief Network for Day-Ahead PV Power Output Forecast
G. W. Chang, Heng‐Jiu Lu
IEEE Transactions on Sustainable Energy (2018) Vol. 11, Iss. 1, pp. 185-194
Closed Access | Times Cited: 93
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