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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:

Ensemble deep learning framework for stock market data prediction (EDLF-DP)
Vaishali Ingle, Sachin N. Deshmukh
Global Transitions Proceedings (2021) Vol. 2, Iss. 1, pp. 47-66
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review
Matin N. Ashtiani, Bijan Raahemi
Expert Systems with Applications (2023) Vol. 217, pp. 119509-119509
Closed Access | Times Cited: 92
Integrating EEMD and ensemble CNN with X (Twitter) sentiment for enhanced stock price predictions
Nabanita Das, Bikash Sadhukhan, Susmit Sekhar Bhakta, et al.
Social Network Analysis and Mining (2024) Vol. 14, Iss. 1
Closed Access | Times Cited: 6
Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately
Armin Lawi, Hendra Mesra, Supri Amir
Journal Of Big Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 23
Implementing a novel strategy to mitigate the risk associated with stock market investments: An examination of the KOSPI instance
Qiaoqiao Chen
Intelligent Decision Technologies (2025)
Closed Access
A Deep Reinforcement Learning-Based Decision Support System for Automated Stock Market Trading
Yasmeen Ansari, Sadaf Yasmin, Sheneela Naz, et al.
IEEE Access (2022) Vol. 10, pp. 127469-127501
Open Access | Times Cited: 19
Hyper Capsule LSTM-Gated GAN with Bayesian Optimized SVM for Cloud-based Stock Market Price Prediction in Big Data Environments
M. Nivetha, C. Jeganathan, Abdelkrim Khadir
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 2
Open Access
A Comparative Analysis of Machine Learning Algorithms in Stock Prediction: A Case Study of Moroccan All Shares Index
Mohamed Abijoue, Mohammed Benkhalifa, Hajar El Hannach
Lecture notes in networks and systems (2025), pp. 19-27
Closed Access
A novel study on deep learning framework to predict and analyze the financial time series information
Yang Shuigen
Future Generation Computer Systems (2021) Vol. 125, pp. 812-819
Closed Access | Times Cited: 23
An Analytic Review on Stock Market Price Prediction using Machine Learning and Deep Learning Techniques
Swarnalata Rath, Nilima R. Das, Binod Kumar Pattanayak
Recent Patents on Engineering (2023) Vol. 18, Iss. 2
Closed Access | Times Cited: 8
LT-SMF: long term stock market price trend prediction using optimal hybrid machine learning technique
K. Venkateswararao, B. Venkata Ramana Reddy
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5365-5402
Closed Access | Times Cited: 13
Data Driven Artificial Neural Network LSTM Hybrid Predictive Model Applied for International Stock Index Prediction
Ashkan Safari
(2022), pp. 115-120
Closed Access | Times Cited: 9
Enhancing stock market prediction using three-phase classifier and EM-EPO optimization with news feeds and historical data
Shilpa Dixit, Nitasha Soni
Multimedia Tools and Applications (2023) Vol. 83, Iss. 13, pp. 37859-37887
Closed Access | Times Cited: 4
Hybrid Machine Learning Model for Predicting NASDAQ Composite Index
Zakia Zouaghia, Zahra Kodia, Lamjed Ben Saïd
2022 International Symposium on Networks, Computers and Communications (ISNCC) (2023) Vol. 3, pp. 1-6
Closed Access | Times Cited: 4
A Compact Literature Review on Stock Market Prediction
Yalanati Ayyappa, A. P. Siva Kumar
2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA) (2022) Vol. 176, pp. 1336-1347
Closed Access | Times Cited: 7
Application of artificial intelligence technology in financial data inspection and manufacturing bond default prediction in small and medium-sized enterprises (SMEs)
Chenxiang Zhang, Fengrui Zhang, Ningyan Chen, et al.
Operations Management Research (2022) Vol. 15, Iss. 3-4, pp. 941-952
Closed Access | Times Cited: 6
Hybrid optimization enabled deep learning and spark architecture using big data analytics for stock market forecasting
Pendela Kanchanamala, Ramesh Karnati, Palagiri Vijaya Bhaskar Reddy
Concurrency and Computation Practice and Experience (2023) Vol. 35, Iss. 8
Closed Access | Times Cited: 3
Automatic Detection of Covid-19 with Bidirectional LSTM Network Using Deep Features Extracted from Chest X-ray Images
Kemal Akyol, Baha Şen
Interdisciplinary Sciences Computational Life Sciences (2021) Vol. 14, Iss. 1, pp. 89-100
Open Access | Times Cited: 7
A comparative study of different neural networks in predicting gross domestic product
Han Lai
Journal of Intelligent Systems (2022) Vol. 31, Iss. 1, pp. 601-610
Open Access | Times Cited: 4
Transfer Learning Framework for Forecasting Fresh Produce Yield and Price
Islam Nasr, Lobna Nassar, Fakhri Karray
2022 International Joint Conference on Neural Networks (IJCNN) (2022), pp. 1-8
Closed Access | Times Cited: 4
Decision Support Machine- A Hybrid Model for Sentiment Analysis of News Headlines of Stock Market
Kirti Sharma, Rajni Bhalla
International journal of electrical and computer engineering systems (2022) Vol. 13, Iss. 9, pp. 791-798
Open Access | Times Cited: 3
Real Estate Market Prediction Using Deep Learning Models
Ramchandra Rimal, Binod Rimal, Hum Nath Bhandari, et al.
Annals of Data Science (2024)
Closed Access
A Comparative Review on Stock Market Prediction Using Artificial Intelligence
Pulok Sarker, Abu Sayed, Abu Bakar Siddique, et al.
Malaysian Journal of Science and Advanced Technology (2024), pp. 383-404
Open Access
A multivariate LSTM-based deep learning model for stock market prediction
Samuel Ibukun Olotu
Applied and Computational Engineering (2023) Vol. 2, Iss. 1, pp. 965-973
Open Access | Times Cited: 1
DEHypGpOls: A Genetic Programming with Evolutionary Hyper-Parameter Optimization and its Application for Stock Market Trend Prediction
Davut Ari, Barış Baykant Alagöz
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
Meta-Heuristic-Based Hybrid Resnet with Recurrent Neural Network for Enhanced Stock Market Prediction
Sowmya Kethi Reddi, Ch. Ramesh Babu
International Journal of Distributed Systems and Technologies (2022) Vol. 13, Iss. 1, pp. 1-28
Closed Access | Times Cited: 1
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