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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:

Empirical Mode Decomposition based ensemble deep learning for load demand time series forecasting
Xueheng Qiu, Ye Ren, Ponnuthurai Nagaratnam Suganthan, et al.
Applied Soft Computing (2017) Vol. 54, pp. 246-255
Closed Access | Times Cited: 413

Showing 1-25 of 413 citing articles:

Ensemble deep learning: A review
M. A. Ganaie, Minghui Hu, A. K. Malik, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105151-105151
Open Access | Times Cited: 1195
Deep Learning for Time Series Forecasting: A Survey
J. F. Torres, Dalil Hadjout, Abderrazak Sebaa, et al.
Big Data (2020) Vol. 9, Iss. 1, pp. 3-21
Closed Access | Times Cited: 506
LSTM-based traffic flow prediction with missing data
Yan Tian, Kaili Zhang, LI Jian-yuan, et al.
Neurocomputing (2018) Vol. 318, pp. 297-305
Closed Access | Times Cited: 437
Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data
Kangyang Chen, Hexia Chen, Chuanlong Zhou, et al.
Water Research (2019) Vol. 171, pp. 115454-115454
Closed Access | Times Cited: 423
A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Sheraz Aslam, Herodotos Herodotou, Syed Muhammad Mohsin, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 144, pp. 110992-110992
Closed Access | Times Cited: 400
Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques
Mengmeng Cai, Manisa Pipattanasomporn, Saifur Rahman
Applied Energy (2018) Vol. 236, pp. 1078-1088
Closed Access | Times Cited: 396
Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods
Erick Meira, Fernando Luiz Cyrino Oliveira
Energy (2017) Vol. 144, pp. 776-788
Closed Access | Times Cited: 376
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
Tanveer Ahmad, Hongcai Zhang, Biao Yan
Sustainable Cities and Society (2020) Vol. 55, pp. 102052-102052
Closed Access | Times Cited: 368
Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization
Jie Chen, Guo‐Qiang Zeng, Wuneng Zhou, et al.
Energy Conversion and Management (2018) Vol. 165, pp. 681-695
Closed Access | Times Cited: 365
Wind power prediction using deep neural network based meta regression and transfer learning
Aqsa Saeed Qureshi, Asifullah Khan, Aneela Zameer, et al.
Applied Soft Computing (2017) Vol. 58, pp. 742-755
Closed Access | Times Cited: 342
Deterministic and probabilistic forecasting of photovoltaic power based on deep convolutional neural network
Huaizhi Wang, Haiyan Yi, Jianchun Peng, et al.
Energy Conversion and Management (2017) Vol. 153, pp. 409-422
Open Access | Times Cited: 328
A Review of Deep Learning Models for Time Series Prediction
Zhongyang Han, Jun Zhao, Henry Leung, et al.
IEEE Sensors Journal (2019) Vol. 21, Iss. 6, pp. 7833-7848
Closed Access | Times Cited: 308
Electric load forecasting based on deep learning and optimized by heuristic algorithm in smart grid
Ghulam Hafeez, Khurram Saleem Alimgeer, Imran Khan
Applied Energy (2020) Vol. 269, pp. 114915-114915
Closed Access | Times Cited: 285
Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network
Jun Wu, Kui Hu, Yiwei Cheng, et al.
ISA Transactions (2019) Vol. 97, pp. 241-250
Closed Access | Times Cited: 277
Short term electricity load forecasting using a hybrid model
Jinliang Zhang, Yi‐Ming Wei, Dezhi Li, et al.
Energy (2018) Vol. 158, pp. 774-781
Open Access | Times Cited: 274
A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
Abdullah Al Mamun, Md. Sohel, Naeem Mohammad, et al.
IEEE Access (2020) Vol. 8, pp. 134911-134939
Open Access | Times Cited: 254
Exploring the use of deep neural networks for sales forecasting in fashion retail
A.L.D. Loureiro, Vera Miguéis, Lucas F. M. da Silva
Decision Support Systems (2018) Vol. 114, pp. 81-93
Closed Access | Times Cited: 210
Recurrent Broad Learning Systems for Time Series Prediction
Meiling Xu, Min Han, C. L. Philip Chen, et al.
IEEE Transactions on Cybernetics (2018) Vol. 50, Iss. 4, pp. 1405-1417
Closed Access | Times Cited: 201
Deep learning methods and applications for electrical power systems: A comprehensive review
Asiye Kaymaz Özcanlı, Fatma Yaprakdal, Mustafa Baysal
International Journal of Energy Research (2020) Vol. 44, Iss. 9, pp. 7136-7157
Open Access | Times Cited: 179
A data-driven strategy for short-term electric load forecasting using dynamic mode decomposition model
Neethu Mohan, K. P. Soman, S. Sachin Kumar
Applied Energy (2018) Vol. 232, pp. 229-244
Closed Access | Times Cited: 176
Stock Market Trend Prediction Using High-Order Information of Time Series
Min Wen, Ping Li, Lingfei Zhang, et al.
IEEE Access (2019) Vol. 7, pp. 28299-28308
Open Access | Times Cited: 159
Predicting Heavy Metal Adsorption on Soil with Machine Learning and Mapping Global Distribution of Soil Adsorption Capacities
Hongrui Yang, Kuan Huang, Kai Zhang, et al.
Environmental Science & Technology (2021) Vol. 55, Iss. 20, pp. 14316-14328
Closed Access | Times Cited: 158
Clustering-based anomaly detection in multivariate time series data
Jingbo Li, Hesam Izakian, Witold Pedrycz, et al.
Applied Soft Computing (2020) Vol. 100, pp. 106919-106919
Closed Access | Times Cited: 152
A Survey on ensemble learning under the era of deep learning
Yongquan Yang, Haijun Lv, Ning Chen
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5545-5589
Closed Access | Times Cited: 149
Fault diagnosis of rolling bearing of wind turbines based on the Variational Mode Decomposition and Deep Convolutional Neural Networks
Zifei Xu, Chun Li, Yang Yang
Applied Soft Computing (2020) Vol. 95, pp. 106515-106515
Open Access | Times Cited: 143
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