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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 novel ensemble deep learning model with dynamic error correction and multi-objective ensemble pruning for time series forecasting
Shuai Zhang, Yong Chen, Wenyu Zhang, et al.
Information Sciences (2020) Vol. 544, pp. 427-445
Closed Access | Times Cited: 110

Showing 1-25 of 110 citing articles:

Building energy prediction using artificial neural networks: A literature survey
Chujie Lu, Sihui Li, Zhengjun Lu
Energy and Buildings (2021) Vol. 262, pp. 111718-111718
Closed Access | Times Cited: 148
Bayesian optimization based dynamic ensemble for time series forecasting
Liang Du, Ruobin Gao, Ponnuthurai Nagaratnam Suganthan, et al.
Information Sciences (2022) Vol. 591, pp. 155-175
Closed Access | Times Cited: 140
An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices
Amadu Fullah Kamara, Enhong Chen, Zhen Pan
Information Sciences (2022) Vol. 594, pp. 1-19
Closed Access | Times Cited: 71
Missing value imputation in multivariate time series with end-to-end generative adversarial networks
Ying Zhang, Baohang Zhou, Xiangrui Cai, et al.
Information Sciences (2020) Vol. 551, pp. 67-82
Closed Access | Times Cited: 98
Prediction of heating energy consumption with operation pattern variables for non-residential buildings using LSTM networks
Jihoon Jang, Jinmog Han, Seung-Bok Leigh
Energy and Buildings (2021) Vol. 255, pp. 111647-111647
Closed Access | Times Cited: 86
Multi-step influenza outbreak forecasting using deep LSTM network and genetic algorithm
Ahmet Kara
Expert Systems with Applications (2021) Vol. 180, pp. 115153-115153
Closed Access | Times Cited: 58
A novel ensemble model based on artificial intelligence and mixed-frequency techniques for wind speed forecasting
Wendong Yang, Zhirui Tian, Hao Yan
Energy Conversion and Management (2021) Vol. 252, pp. 115086-115086
Closed Access | Times Cited: 58
Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models
Nemesio Fava Sopelsa Neto, Stéfano Frizzo Stefenon, Luiz Henrique Meyer, et al.
Sensors (2022) Vol. 22, Iss. 16, pp. 6121-6121
Open Access | Times Cited: 54
Fair-AdaBoost: Extending AdaBoost method to achieve fair classification
Xiaoling Huang, Zhenghui Li, Yilun Jin, et al.
Expert Systems with Applications (2022) Vol. 202, pp. 117240-117240
Closed Access | Times Cited: 52
Effective machine learning model combination based on selective ensemble strategy for time series forecasting
Sheng-Xiang Lv, Lu Peng, Huanling Hu, et al.
Information Sciences (2022) Vol. 612, pp. 994-1023
Closed Access | Times Cited: 50
Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting
Wendong Yang, Mengying Hao, Hao Yan
Information Sciences (2022) Vol. 622, pp. 560-586
Closed Access | Times Cited: 42
Dynamic graph convolutional networks based on spatiotemporal data embedding for traffic flow forecasting
Wenyu Zhang, Kun Zhu, Shuai Zhang, et al.
Knowledge-Based Systems (2022) Vol. 250, pp. 109028-109028
Closed Access | Times Cited: 41
Dynamic adaptive encoder-decoder deep learning networks for multivariate time series forecasting of building energy consumption
Jing Guo, Penghui Lin, Limao Zhang, et al.
Applied Energy (2023) Vol. 350, pp. 121803-121803
Closed Access | Times Cited: 32
Towards Economic Sustainability: A Comprehensive Review of Artificial Intelligence and Machine Learning Techniques in Improving the Accuracy of Stock Market Movements
Atoosa Rezaei, Iheb Abdellatif, Amjad Umar
International Journal of Financial Studies (2025) Vol. 13, Iss. 1, pp. 28-28
Open Access | Times Cited: 1
An adaptive hybrid system using deep learning for wind speed forecasting
Paulo S. G. de Mattos Neto, João Fausto Lorenzato de Oliveira, Domingos S. de O. Santos, et al.
Information Sciences (2021) Vol. 581, pp. 495-514
Closed Access | Times Cited: 42
Models of Electricity Price Forecasting: Bibliometric Research
Tomasz Zema, Adam Sulich
Energies (2022) Vol. 15, Iss. 15, pp. 5642-5642
Open Access | Times Cited: 34
Network self attention for forecasting time series
Yuntong Hu, Fuyuan Xiao
Applied Soft Computing (2022) Vol. 124, pp. 109092-109092
Closed Access | Times Cited: 33
Cluster-based demand forecasting using Bayesian model averaging: An ensemble learning approach
Mahya Seyedan, Fereshteh Mafakheri, Chun Wang
Decision Analytics Journal (2022) Vol. 3, pp. 100033-100033
Open Access | Times Cited: 31
Wind speed forecasting using multi-scale feature adaptive extraction ensemble model with error regression correction
Jun Chen, Hui Liu, Chao Chen, et al.
Expert Systems with Applications (2022) Vol. 207, pp. 117358-117358
Closed Access | Times Cited: 30
Surrogate-Assisted and Filter-Based Multiobjective Evolutionary Feature Selection for Deep Learning
Raquel Espinosa, Fernando Jiménez, José Palma
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 7, pp. 9591-9605
Closed Access | Times Cited: 19
Order-up-to-level inventory optimization model using time-series demand forecasting with ensemble deep learning
Mahya Seyedan, Fereshteh Mafakheri, Chun Wang
Supply Chain Analytics (2023) Vol. 3, pp. 100024-100024
Open Access | Times Cited: 17
Optimizing Time-Series forecasting using stacked deep learning framework with enhanced adaptive moment estimation and error correction
Ravi Prakash Varshney, Dilip Kumar Sharma
Expert Systems with Applications (2024) Vol. 249, pp. 123487-123487
Closed Access | Times Cited: 6
Wind power forecasting based on time series model using deep machine learning algorithms
Chandran Venkatesan, Chandrashekhar K. Patil, Anto Merline Manoharan, et al.
Materials Today Proceedings (2021) Vol. 47, pp. 115-126
Closed Access | Times Cited: 38
A Stacking Ensemble Deep Learning Model for Building Extraction from Remote Sensing Images
Duanguang Cao, Hanfa Xing, Man Sing Wong, et al.
Remote Sensing (2021) Vol. 13, Iss. 19, pp. 3898-3898
Open Access | Times Cited: 37
A relationship-aligned transfer learning algorithm for time series forecasting
Rui Ye, Qun Dai
Information Sciences (2022) Vol. 593, pp. 17-34
Closed Access | Times Cited: 27
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