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:

COMPARING THE PREDICTION ACCURACY OF LSTM AND ARIMA MODELS FOR TIME-SERIES WITH PERMANENT FLUCTUATION
Ghahreman Abdoli, Mohsen Mehrara, Mohammad Ebrahim Ardalani
Gênero & Direito (2020) Vol. 9, Iss. 2
Open Access | Times Cited: 15

Showing 15 citing articles:

Advancing air quality forecasting in Abu Dhabi, UAE using time series models
Mona S. Ramadan, Abdelgadir Abuelgasim, Naeema Al Hosani
Frontiers in Environmental Science (2024) Vol. 12
Open Access | Times Cited: 7

Application of Convolutional Neural Networks and Recurrent Neural Networks in Food Safety
Haohan Ding, Haoke Hou, Long Wang, et al.
Foods (2025) Vol. 14, Iss. 2, pp. 247-247
Open Access

Prediction of Macroeconomic Growth Using Backpropagation Algorithms: A Review
Nur Fitri Hidayanti, Syaharuddin Syaharuddin, Nurul Hidayati Indra Ningsih, et al.
International Journal of Scientific Research and Management (IJSRM) (2025) Vol. 13, Iss. 01, pp. 8255-8266
Open Access

Prediction of Stock Price Using Statistical and Ensemble learning Models: A Comparative Study
Ayushman Durgapal, Vrince Vimal
2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (2021), pp. 1-6
Closed Access | Times Cited: 27

Long-Term Forecasting of Euro-Dollar Exchange Rates Using the ARIMA Model and Multilayer Perceptron
Gladys R. Velasco Chasipanta, Nadia N. Sánchez-Pozo
Ingénierie des systèmes d information (2024) Vol. 29, Iss. 1, pp. 125-139
Open Access | Times Cited: 1

Multivariate Time Series Sensor Feature Forecasting Using Deep Bidirectional LSTM
B. Sirisha, Surakanti Naveena, Greeshma Palanki, et al.
Procedia Computer Science (2023) Vol. 218, pp. 1374-1383
Open Access | Times Cited: 3

Bitcoin daily close price prediction using optimized grid search method
Marzieh Rostami, Mahdi Bahaghighat, Morteza Mohammadi Zanjireh
Acta Universitatis Sapientiae Informatica (2021) Vol. 13, Iss. 2, pp. 265-287
Open Access | Times Cited: 8

Estimating and tuning adaptive action plans for the control of smart interconnected poultry condominiums
Darlan F. Klotz, Richardson Ribeiro, Fabrício Enembreck, et al.
Expert Systems with Applications (2021) Vol. 187, pp. 115876-115876
Closed Access | Times Cited: 4

Comparative Analysis of ARIMA and LSTM Models for Predicting Physical Fatigue in Bandung Workers
Kiki Dwi Prasetyo, Rifki Wijaya, Gia Septiana Wulandari
JURNAL MEDIA INFORMATIKA BUDIDARMA (2024) Vol. 8, Iss. 1, pp. 528-528
Open Access

Multivariate stock market forecasting using lstm on Indonesian banking stock market
Kenrick, Steffano Claus Ivancio, Elisabeth Isabellini, et al.
Procedia Computer Science (2024) Vol. 245, pp. 1047-1056
Open Access

Estimating action plans for smart poultry houses
Darlan F. Klotz, Richardson Ribeiro, Fabrício Enembreck, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 2

Stock Market Price Movement Forecasting on BURSA Malaysia using Machine Learning Approach
Leong Jia Ling, Seetha Letchumy M. Belaidan
2021 14th International Conference on Developments in eSystems Engineering (DeSE) (2021), pp. 102-108
Closed Access | Times Cited: 2

Predicting the Workload in Debt Collections to Improve the Efficiency of Manpower Planning
Pornpimol Chaiwuttisak
Lecture notes in networks and systems (2022), pp. 675-684
Closed Access

Share Buyback Prediction using LSTM on Malaysian Stock Market
Muhammad Zahid bin Hilmi, Ahmad Kamil Mahmood, Abdul Moin, et al.
(2021), pp. 390-395
Closed Access

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