Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 Recurrent Neural Network Based Probabilistic Wind Speed Forecasting Approach
Lilin Cheng, Haixiang Zang, Tao Ding, et al.
Energies (2018) Vol. 11, Iss. 8, pp. 1958-1958
Open Access | Times Cited: 81

Showing 1-25 of 81 citing articles:

Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
IEEE Transactions on Knowledge and Data Engineering (2020) Vol. 34, Iss. 8, pp. 3681-3700
Open Access | Times Cited: 536
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: 397
Data processing strategies in wind energy forecasting models and applications: A comprehensive review
Hui Liu, Chao Chen
Applied Energy (2019) Vol. 249, pp. 392-408
Closed Access | Times Cited: 295
Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods
Hui Liu, Chao Chen, Xinwei Lv, et al.
Energy Conversion and Management (2019) Vol. 195, pp. 328-345
Closed Access | Times Cited: 250
Graph Neural Controlled Differential Equations for Traffic Forecasting
Jeongwhan Choi, Hwangyong Choi, JeeHyun Hwang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 6, pp. 6367-6374
Open Access | Times Cited: 181
A review on multi-objective optimization framework in wind energy forecasting techniques and applications
Hui Liu, Ye Li, Zhu Duan, et al.
Energy Conversion and Management (2020) Vol. 224, pp. 113324-113324
Closed Access | Times Cited: 154
A novel deep learning ensemble model with data denoising for short-term wind speed forecasting
Zhiyun Peng, Sui Peng, Lidan Fu, et al.
Energy Conversion and Management (2020) Vol. 207, pp. 112524-112524
Closed Access | Times Cited: 143
Load Forecasting Techniques for Power System: Research Challenges and Survey
Naqash Ahmad, Yazeed Yasin Ghadi, Muhammad Adnan, et al.
IEEE Access (2022) Vol. 10, pp. 71054-71090
Open Access | Times Cited: 132
Data-driven prediction and optimization toward net-zero and positive-energy buildings: A systematic review
SeyedehNiloufar Mousavi, María Guadalupe Villarreal-Marroquín, Mostafa Hajiaghaei–Keshteli, et al.
Building and Environment (2023) Vol. 242, pp. 110578-110578
Closed Access | Times Cited: 51
A review of applications of artificial intelligent algorithms in wind farms
Yirui Wang, Yang Yu, Shuyang Cao, et al.
Artificial Intelligence Review (2019) Vol. 53, Iss. 5, pp. 3447-3500
Closed Access | Times Cited: 106
State-of-the-art one-stop handbook on wind forecasting technologies: An overview of classifications, methodologies, and analysis
Bo Yang, Linen Zhong, Jingbo Wang, et al.
Journal of Cleaner Production (2020) Vol. 283, pp. 124628-124628
Closed Access | Times Cited: 86
Battery energy storage sizing based on a model predictive control strategy with operational constraints to smooth the wind power
Minjian Cao, Qingshan Xu, Xiaoyang Qin, et al.
International Journal of Electrical Power & Energy Systems (2019) Vol. 115, pp. 105471-105471
Closed Access | Times Cited: 83
Short-term average wind speed and turbulent standard deviation forecasts based on one-dimensional convolutional neural network and the integrate method for probabilistic framework
Xinyu Zhao, Na Jiang, Jinfu Liu, et al.
Energy Conversion and Management (2019) Vol. 203, pp. 112239-112239
Closed Access | Times Cited: 80
A novel loss function of deep learning in wind speed forecasting
Xi Chen, Ruyi Yu, Sajid Ullah, et al.
Energy (2021) Vol. 238, pp. 121808-121808
Closed Access | Times Cited: 63
Probabilistic wind power forecasting using selective ensemble of finite mixture Gaussian process regression models
Huaiping Jin, Lixian Shi, Xiangguang Chen, et al.
Renewable Energy (2021) Vol. 174, pp. 1-18
Closed Access | Times Cited: 61
Wind speed estimation using novelty hybrid adaptive estimation model based on decomposition and deep learning methods (ICEEMDAN-CNN)
Cem Emeksiz, Mustafa Tan
Energy (2022) Vol. 249, pp. 123785-123785
Closed Access | Times Cited: 44
An overview of deterministic and probabilistic forecasting methods of wind energy
Yuying Xie, Chaoshun Li, Mengying Li, et al.
iScience (2022) Vol. 26, Iss. 1, pp. 105804-105804
Open Access | Times Cited: 42
Artificial Intelligence in Wind Speed Forecasting: A Review
Sandra Minerva Valdivia-Bautista, José A. Domínguez‐Navarro, Marco Pérez‐Cisneros, et al.
Energies (2023) Vol. 16, Iss. 5, pp. 2457-2457
Open Access | Times Cited: 37
Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review
Nathan Oaks Farrar, Mohd. Hasan Ali, Dipankar Dasgupta
Energies (2023) Vol. 16, Iss. 3, pp. 1530-1530
Open Access | Times Cited: 27
Towards smart energy management for community microgrids: Leveraging deep learning in probabilistic forecasting of renewable energy sources
Jhon J. Quiñones, Luis R. Pineda, Jason K. Ostanek, et al.
Energy Conversion and Management (2023) Vol. 293, pp. 117440-117440
Open Access | Times Cited: 26
A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems
Kinza Fida, Usman Abbasi, Muhammad Adnan, et al.
Results in Engineering (2024) Vol. 23, pp. 102773-102773
Open Access | Times Cited: 7
Novel Multi-Time Scale Deep Learning Algorithm for Solar Irradiance Forecasting
N. Jayalakshmi, R. Shankar, Umashankar Subramaniam, et al.
Energies (2021) Vol. 14, Iss. 9, pp. 2404-2404
Open Access | Times Cited: 47
Advancements in wind power forecasting: A comprehensive review of artificial intelligence-based approaches
Krishan Kumar, Priti Prabhakar, Avnesh Verma, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 5
A cooperative ensemble method for multistep wind speed probabilistic forecasting
Yaoyao He, Yun Wang, Shuo Wang, et al.
Chaos Solitons & Fractals (2022) Vol. 162, pp. 112416-112416
Closed Access | Times Cited: 24
A Novel Deep Learning Approach for Short Term Photovoltaic Power Forecasting Based on GRU-CNN Model
Mohammed Sabri, Mohammed El Hassouni
E3S Web of Conferences (2022) Vol. 336, pp. 00064-00064
Open Access | Times Cited: 22
Page 1 - Next Page

Scroll to top