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:

A novel selective ensemble system for wind speed forecasting: From a new perspective of multiple predictors for subseries
Sibo Yang, Wendong Yang, Xiaodi Wang, et al.
Energy Conversion and Management (2023) Vol. 294, pp. 117590-117590
Closed Access | Times Cited: 17

Showing 17 citing articles:

Ultra-short-term wind power probabilistic forecasting based on an evolutionary non-crossing multi-output quantile regression deep neural network
Jianhua Zhu, Yaoyao He, Xiaodong Yang, et al.
Energy Conversion and Management (2024) Vol. 301, pp. 118062-118062
Closed Access | Times Cited: 20

An innovative interpretable combined learning model for wind speed forecasting
Pei Du, Dongchuan Yang, Yanzhao Li, et al.
Applied Energy (2024) Vol. 358, pp. 122553-122553
Closed Access | Times Cited: 19

Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S
Xiaoying Sun, Haizhong Liu
Energy (2024) Vol. 305, pp. 132228-132228
Closed Access | Times Cited: 16

River Water Temperature Prediction Using a Hybrid Model Based on Variational Mode Decomposition (VMD) and Outlier Robust Extreme Learning Machine
Ehsan Mirzania, Thendiyath Roshni, Mohammad Ali Ghorbani, et al.
Environmental Processes (2024) Vol. 11, Iss. 3
Closed Access | Times Cited: 5

Optimising wellbore annular leakage detection and diagnosis model: A signal feature enhancement and hybrid intelligent optimised LSSVM approach
Zhongxi Zhu, Hong Liu, Wanneng Lei, et al.
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112451-112451
Closed Access

Enhanced forecasting method for realized volatility of energy futures prices: A secondary decomposition-based deep learning model
Hao Gong, H. Y. Xing, Qianwen Wang
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110321-110321
Closed Access

Remaining useful life estimation based on selective ensemble of deep neural networks with diversity
Tangbin Xia, Dongyang Han, Yimin Jiang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102608-102608
Closed Access | Times Cited: 3

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy
Yi Yang, Qianyi Xing, Kang Wang, et al.
Applied Energy (2023) Vol. 356, pp. 122341-122341
Closed Access | Times Cited: 7

Developing an interpretable wind power forecasting system using a transformer network and transfer learning
Chaonan Tian, Tong Niu, Tao Li
Energy Conversion and Management (2024) Vol. 323, pp. 119155-119155
Closed Access | Times Cited: 1

Electricity Price Forecasting Combined with Wavelet Packet Decomposition and a Hybrid Deep Neural Network in Spot Market
Heping Jia, Yuchen Guo, Xiao‐Bin Zhang, et al.
Research Square (Research Square) (2024)
Open Access

Forecasting sovereign CDS spreads with a regime‐switching combination method
Jianping Li, Qianqian Feng, Jun Hao, et al.
Journal of Forecasting (2024) Vol. 43, Iss. 8, pp. 3089-3103
Open Access

A novel hybrid model for multi-step-ahead forecasting of wind speed based on univariate data feature enhancement
Yaqi Wang, Xiaomeng Zhao, Zheng Li, et al.
Energy (2024), pp. 133515-133515
Closed Access

An innovative memory-enhanced Elman neural network-based selective ensemble system for short-term wind speed prediction
Xue-Yi Ai, Tao Feng, Gan Wei, et al.
Applied Energy (2024) Vol. 380, pp. 125108-125108
Closed Access

Page 1

Scroll to top