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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:

Forecasting container throughput with long short-term memory networks
Sonali Shankar, P. Vigneswara Ilavarasan, Sushil Punia, et al.
Industrial Management & Data Systems (2019) Vol. 120, Iss. 3, pp. 425-441
Closed Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions
Κωνσταντίνος Νικολόπουλος, Sushil Punia, Andreas Schäfers, et al.
European Journal of Operational Research (2020) Vol. 290, Iss. 1, pp. 99-115
Open Access | Times Cited: 444
Improving time series forecasting using LSTM and attention models
Hossein Abbasimehr, Reza Paki
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 13, Iss. 1, pp. 673-691
Closed Access | Times Cited: 162
Applications of machine learning methods in port operations – A systematic literature review
Siyavash Filom, Amir Mohammad Amiri, Saiedeh Razavi
Transportation Research Part E Logistics and Transportation Review (2022) Vol. 161, pp. 102722-102722
Closed Access | Times Cited: 83
Deep learning applications in manufacturing operations: a review of trends and ways forward
Saumyaranjan Sahoo, Satish Kumar, Mohammad Zoynul Abedin, et al.
Journal of Enterprise Information Management (2022) Vol. 36, Iss. 1, pp. 221-251
Closed Access | Times Cited: 54
Predictive analytics for demand forecasting: A deep learning-based decision support system
Sushil Punia, Sonali Shankar
Knowledge-Based Systems (2022) Vol. 258, pp. 109956-109956
Closed Access | Times Cited: 48
Applications of deep learning into supply chain management: a systematic literature review and a framework for future research
Fahimeh Hosseinnia Shavaki, Ali Ebrahimi Ghahnavieh
Artificial Intelligence Review (2022) Vol. 56, Iss. 5, pp. 4447-4489
Open Access | Times Cited: 40
A novel hybrid deep-learning framework for medium-term container throughput forecasting: an application to China’s Guangzhou, Qingdao and Shanghai hub ports
Di Zhang, Xinyuan Li, Chengpeng Wan, et al.
Maritime Economics & Logistics (2024) Vol. 26, Iss. 1, pp. 44-73
Closed Access | Times Cited: 8
A cross-temporal hierarchical framework and deep learning for supply chain forecasting
Sushil Punia, Surya Prakash Singh, Jitendra Madaan
Computers & Industrial Engineering (2020) Vol. 149, pp. 106796-106796
Closed Access | Times Cited: 54
Forecasting container throughput of major Asian ports using the Prophet and hybrid time series models
Ziaul Haque Munim, Cemile Solak Fışkın, Bikram Nepal, et al.
The Asian Journal of Shipping and Logistics (2023) Vol. 39, Iss. 2, pp. 67-77
Open Access | Times Cited: 17
Development of a Time Series E-Commerce Sales Prediction Method for Short-Shelf-Life Products Using GRU-LightGBM
Yong Chen, Xian Xie, Zhi Pei, et al.
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 866-866
Open Access | Times Cited: 7
Forecast combination using grey relational analysis and Choquet fuzzy integral for container throughput forecasting
Geng Wu, Yi‐Chung Hu, Yu‐Jing Chiu, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124170-124170
Closed Access | Times Cited: 7
From predictive to prescriptive analytics: A data-driven multi-item newsvendor model
Sushil Punia, Surya Prakash Singh, Jitendra Madaan
Decision Support Systems (2020) Vol. 136, pp. 113340-113340
Closed Access | Times Cited: 45
Leveraging machine learning and optimization models for enhanced seaport efficiency
Mahdi Jahangard, Ying Xie, Yuanjun Feng
Maritime Economics & Logistics (2025)
Open Access
Prediction of container throughput at Thailand’s major ports with error correction and parameter selection techniques emphasizes optimal smoothing period
Thoranin Sujjaviriyasup
Maritime Business Review (2025)
Open Access
Deep learning-based estimation of truck Turn Around Time at container port
Buhyun Shin, Y.B. Min, Gunwoo Lee, et al.
Maritime Policy & Management (2025), pp. 1-17
Closed Access
Short-term forecasting for port throughput time series based on multi-modal fuzzy information granule
Fang Li, Wen H. Tong, Xiyang Yang
Applied Soft Computing (2025), pp. 112957-112957
Closed Access
Artificial intelligence driven demand forecasting: an application to the electricity market
Marco Repetto, Cinzia Colapinto, Muhammad Usman Tariq
Annals of Operations Research (2024)
Closed Access | Times Cited: 4
Analyzing and Forecasting Container Throughput With a Hybrid Decomposition‐Reconstruction‐Ensemble Method: A Study of Two China Ports
Xiao Yi, Sheng Wu, Chen He, et al.
Journal of Forecasting (2025)
Closed Access
Deep learning-based container throughput forecasting: a triple bottom line approach
Sonali Shankar, Sushil Punia, P. Vigneswara Ilavarasan
Industrial Management & Data Systems (2021) Vol. 121, Iss. 10, pp. 2100-2117
Closed Access | Times Cited: 21
Container terminal daily gate in and gate out forecasting using machine learning methods
Jiahuan Jin, Mingyu Ma, Huan Jin, et al.
Transport Policy (2022) Vol. 132, pp. 163-174
Closed Access | Times Cited: 14
A multi-variable hybrid system for port container throughput deterministic and uncertain forecasting
Jianzhou Wang, Yuanyuan Shao, He Jiang, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121546-121546
Closed Access | Times Cited: 7
A novel real-time multi-step forecasting system with a three-stage data preprocessing strategy for containerized freight market
Kedong Yin, Hongbo Guo, Wendong Yang
Expert Systems with Applications (2024) Vol. 246, pp. 123141-123141
Closed Access | Times Cited: 2
Hybrid convolutional long short‐term memory models for sales forecasting in retail
Thais de Castro Moraes, Xiaoming Yuan, Ek Peng Chew
Journal of Forecasting (2024) Vol. 43, Iss. 5, pp. 1278-1293
Open Access | Times Cited: 2
A deep learning‐based multivariate decomposition and ensemble framework for container throughput forecasting
Anurag Kulshrestha, Abhishek Yadav, Himanshu Sharma, et al.
Journal of Forecasting (2024) Vol. 43, Iss. 7, pp. 2685-2704
Closed Access | Times Cited: 2
Advancements in Deep Learning Techniques for Time Series Forecasting in Maritime Applications: A Comprehensive Review
Meng Wang, Xinyan Guo, Yanling She, et al.
Information (2024) Vol. 15, Iss. 8, pp. 507-507
Open Access | Times Cited: 2
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