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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:

Deep Learning for Price Movement Prediction Using Convolutional Neural Network and Long Short-Term Memory
Can Yang, Junjie Zhai, Guihua Tao
Mathematical Problems in Engineering (2020) Vol. 2020, pp. 1-13
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
Kyung Keun Yun, Sang Won Yoon, Daehan Won
Expert Systems with Applications (2021) Vol. 186, pp. 115716-115716
Closed Access | Times Cited: 202
BiCuDNNLSTM-1dCNN — A hybrid deep learning-based predictive model for stock price prediction
Anika Kanwal, Man Fai Lau, Sebastian Ng, et al.
Expert Systems with Applications (2022) Vol. 202, pp. 117123-117123
Closed Access | Times Cited: 89
An integrated approach of ensemble learning methods for stock index prediction using investor sentiments
Shangkun Deng, Yingke Zhu, Yiting Yu, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121710-121710
Closed Access | Times Cited: 26
Validating the impact of accounting disclosures on stock market: A deep neural network approach
Prajwal Eachempati, Praveen Ranjan Srivastava, Ajay Kumar, et al.
Technological Forecasting and Social Change (2021) Vol. 170, pp. 120903-120903
Open Access | Times Cited: 42
AEI-DNET: A Novel DenseNet Model with an Autoencoder for the Stock Market Predictions Using Stock Technical Indicators
Saleh Albahli, Tahira Nazir, Awais Mehmood, et al.
Electronics (2022) Vol. 11, Iss. 4, pp. 611-611
Open Access | Times Cited: 37
Machine learning models predicting returns: Why most popular performance metrics are misleading and proposal for an efficient metric
Jean Dessain
Expert Systems with Applications (2022) Vol. 199, pp. 116970-116970
Open Access | Times Cited: 37
Extending machine learning prediction capabilities by explainable AI in financial time series prediction
Taha Buğra Çeli̇k, Özgür İcan, Elif Bulut
Applied Soft Computing (2022) Vol. 132, pp. 109876-109876
Closed Access | Times Cited: 29
Stacked BI-LSTM and E-Optimized CNN-A Hybrid Deep Learning Model for Stock Price Prediction
Swarnalata Rath, Nilima R. Das, Binod Kumar Pattanayak
Optical Memory and Neural Networks (2024) Vol. 33, Iss. 2, pp. 102-120
Closed Access | Times Cited: 5
Predicting Stock Prices in the Pakistan Market Using Machine Learning and Technical Indicators
Hassan Raza, Zafar Akhtar
Modern Finance (2024) Vol. 2, Iss. 2, pp. 46-63
Open Access | Times Cited: 5
Unified noise estimation and denoising algorithm with filters and neural networks for denoising satellite images
Sakshi Anand, Rakesh Sharma
The Imaging Science Journal (2025), pp. 1-14
Closed Access
Optimization of Stock Predictions on Indonesia Stock Exchange: A New Hybrid Deep Learning Method
B. Yudi Dwiandiyanta, Rudy Hartanto, Ridi Ferdiana
Engineering Technology & Applied Science Research (2025) Vol. 15, Iss. 1, pp. 19370-19379
Open Access
Piyasa Yönünün Derin Öğrenme ile Tahmini: E-7 Ülke Borsaları Üzerine Bir Uygulama
Nazif Ayyıldız
Maliye Finans Yazıları (2025), Iss. 123, pp. 92-111
Open Access
Probabilistic analysis of impulse waves generated by large deposits in mountain reservoirs
Huanling Wang, Hangsheng Ma, Yizhe Wu, et al.
Physics of Fluids (2025) Vol. 37, Iss. 4
Closed Access
A hybrid model integrating GRU with artificial rabbit optimization for stock price prediction
Xiaohua Zeng, Wanling Chen
International Journal of Intelligent Computing and Cybernetics (2025)
Closed Access
An improved DenseNet model for prediction of stock market using stock technical indicators
Saleh Albahli, Tahira Nazir, Marriam Nawaz, et al.
Expert Systems with Applications (2023) Vol. 232, pp. 120903-120903
Closed Access | Times Cited: 12
Hybrid wavelet-neural network models for time series
Deniz Kenan Kılıç, Ömür Uğur
Applied Soft Computing (2023) Vol. 144, pp. 110469-110469
Open Access | Times Cited: 11
A Two-Delay Combination Model for Stock Price Prediction
Manlika Ratchagit, Honglei Xu
Mathematics (2022) Vol. 10, Iss. 19, pp. 3447-3447
Open Access | Times Cited: 12
Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction
Andri Pranolo, Yingchi Mao, Aji Prasetya Wibawa, et al.
Knowledge Engineering and Data Science (2022) Vol. 5, Iss. 1, pp. 53-53
Open Access | Times Cited: 11
Deep Learning for Financial Time Series Prediction: A State-of-the-Art Review of Standalone and Hybrid Models
Weisi Chen, Walayat Hussain, Francesco Cauteruccio, et al.
Computer Modeling in Engineering & Sciences (2023) Vol. 139, Iss. 1, pp. 187-224
Open Access | Times Cited: 6
An Ensembling Architecture Incorporating Machine Learning Models and Genetic Algorithm Optimization for Forex Trading
Leonard Loh, Hee Kueh, N. Parikh, et al.
FinTech (2022) Vol. 1, Iss. 2, pp. 100-124
Open Access | Times Cited: 10
An incremental type-2 fuzzy classifier for stock trend prediction
Homeira Shahparast, Sam Hamzeloo, Ehram Safari
Expert Systems with Applications (2022) Vol. 212, pp. 118787-118787
Closed Access | Times Cited: 8
A dynamic scenario‐driven technique for stock price prediction and trading
Yash Thesia, Vidhey Oza, Priyank Thakkar
Journal of Forecasting (2021) Vol. 41, Iss. 3, pp. 653-674
Closed Access | Times Cited: 9
Prediction of the Stock Market From Linguistic Phrases
Prajwal Eachempati, Praveen Ranjan Srivastava
Journal of Database Management (2023) Vol. 34, Iss. 1, pp. 1-22
Open Access | Times Cited: 3
Prediction of stock price movement using an improved NSGA-II-RF algorithm with a three-stage feature engineering process
Xiaohua Zeng, Jieping Cai, Changzhou Liang, et al.
PLoS ONE (2023) Vol. 18, Iss. 6, pp. e0287754-e0287754
Open Access | Times Cited: 3
Predicting price trends combining kinetic energy and deep reinforcement learning
Mahdieh Ghotbi, Morteza Zahedi
Expert Systems with Applications (2023) Vol. 244, pp. 122994-122994
Closed Access | Times Cited: 3
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