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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:

A support vector machine for model selection in demand forecasting applications
Marco A. Villegas, Diego J. Pedregal, Juan R. Trapero
Computers & Industrial Engineering (2018) Vol. 121, pp. 1-7
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

An optimized model using LSTM network for demand forecasting
Hossein Abbasimehr, Mostafa Shabani, Mohsen Yousefi
Computers & Industrial Engineering (2020) Vol. 143, pp. 106435-106435
Closed Access | Times Cited: 389
Machine Learning for industrial applications: A comprehensive literature review
Massimo Bertolini, Davide Mezzogori, Mattia Neroni, et al.
Expert Systems with Applications (2021) Vol. 175, pp. 114820-114820
Closed Access | Times Cited: 348
Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities
Mahya Seyedan, Fereshteh Mafakheri
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 278
Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets
Jyotirmayee Behera, Ajit Kumar Pasayat, Harekrushna Behera, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105843-105843
Closed Access | Times Cited: 65
Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion
Mahdi Abolghasemi, Eric J. Beh, Garth Tarr, et al.
Computers & Industrial Engineering (2020) Vol. 142, pp. 106380-106380
Open Access | Times Cited: 136
UNISON data-driven intermittent demand forecast framework to empower supply chain resilience and an empirical study in electronics distribution
Wenhan Fu, Chen‐Fu Chien
Computers & Industrial Engineering (2019) Vol. 135, pp. 940-949
Closed Access | Times Cited: 106
Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor
Chen‐Fu Chien, Yun-Siang Lin, Sheng-Kai Lin
International Journal of Production Research (2020) Vol. 58, Iss. 9, pp. 2784-2804
Closed Access | Times Cited: 100
The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality
Guo Liang, Weiguo Fang, Qiuhong Zhao, et al.
Computers & Industrial Engineering (2021) Vol. 161, pp. 107598-107598
Closed Access | Times Cited: 73
Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda
Marco Simonetto, Fabio Sgarbossa, Daria Battini, et al.
International Journal of Production Economics (2022) Vol. 253, pp. 108582-108582
Open Access | Times Cited: 57
A state-of-the-art on production planning in Industry 4.0
Dan Luo, Simon Thevenin, Alexandre Dolgui
International Journal of Production Research (2022) Vol. 61, Iss. 19, pp. 6602-6632
Open Access | Times Cited: 47
Review of automated time series forecasting pipelines
Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2022) Vol. 12, Iss. 6
Open Access | Times Cited: 44
Impact of Hyperparameter Tuning on Machine Learning Models in Stock Price Forecasting
Kazi Ekramul Hoque, Hamoud Aljamaan
IEEE Access (2021) Vol. 9, pp. 163815-163830
Open Access | Times Cited: 48
Smart semiconductor manufacturing for pricing, demand planning, capacity portfolio and cost for sustainable supply chain management
Chen‐Fu Chien, Hsuan-An Kuo, Yun-Siang Lin
International Journal of Logistics Research and Applications (2022) Vol. 27, Iss. 1, pp. 193-216
Closed Access | Times Cited: 33
Data-driven time-varying discrete grey model for demand forecasting
Lili Ye, Naiming Xie, Zhongju Shang, et al.
Journal of the Operational Research Society (2025), pp. 1-17
Closed Access
Tourism Demand Forecasting Based on a Hybrid Temporal Neural Network Model for Sustainable Tourism
Yong Cai Zhang, Wee Hoe Tan, Zijian Zeng
Sustainability (2025) Vol. 17, Iss. 5, pp. 2210-2210
Open Access
A new secondary decomposition-ensemble approach with cuckoo search optimization for air cargo forecasting
Hongtao Li, Juncheng Bai, Xiang Cui, et al.
Applied Soft Computing (2020) Vol. 90, pp. 106161-106161
Closed Access | Times Cited: 39
Demand forecasting in supply chains: a review of aggregation and hierarchical approaches
M. Zied Babai, John E. Boylan, Bahman Rostami-Tabar
International Journal of Production Research (2021) Vol. 60, Iss. 1, pp. 324-348
Open Access | Times Cited: 39
Predictive Analysis of a Building’s Power Consumption Based on Digital Twin Platforms
Fengyi Han, Fei Du, Shuo Jiao, et al.
Energies (2024) Vol. 17, Iss. 15, pp. 3692-3692
Open Access | Times Cited: 4
Strategic Insights: Revolutionizing Supply Chain Efficiency Through Big Data Optimization
Varsha Mittal, Preeti Malik
Springer tracts in nature-inspired computing (2025), pp. 211-233
Closed Access
Sustainability performance predictions in supply chains: grey and rough set theoretical approaches
R. Rajesh
Annals of Operations Research (2020) Vol. 310, Iss. 1, pp. 171-200
Closed Access | Times Cited: 35
An ontology-based, general-purpose and Industry 4.0-ready architecture for supporting the smart operator (Part I – Mixed reality case)
Francesco Longo, Giovanni Mirabelli, Letizia Nicoletti, et al.
Journal of Manufacturing Systems (2022) Vol. 64, pp. 594-612
Closed Access | Times Cited: 17
Supply Chain Inventory Management from the Perspective of “Cloud Supply Chain”—A Data Driven Approach
Tan Y, Liyi Gu, Senyu Xu, et al.
Mathematics (2024) Vol. 12, Iss. 4, pp. 573-573
Open Access | Times Cited: 3
From vineyard to table: Uncovering wine quality for sales management through machine learning
Rui Ma, Mao Di, Dongmei Cao, et al.
Journal of Business Research (2024) Vol. 176, pp. 114576-114576
Open Access | Times Cited: 3
Implementation of five machine learning methods to predict the 52-week blood glucose level in patients with type 2 diabetes
Xiaomin Fu, Yuhan Wang, Ryan S. Cates, et al.
Frontiers in Endocrinology (2023) Vol. 13
Open Access | Times Cited: 8
An analysis of critical factors for adopting machine learning in manufacturing supply chains
Revati Gardas, Swati Narwane
Decision Analytics Journal (2023) Vol. 10, pp. 100377-100377
Open Access | Times Cited: 8
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