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.

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Showing 1-25 of 32 citing articles:

DTTR: Encoding and decoding monthly runoff prediction model based on deep temporal attention convolution and multimodal fusion
Wenchuan Wang, Wei-can Tian, Xiao-xue Hu, et al.
Journal of Hydrology (2024) Vol. 643, pp. 131996-131996
Closed Access | Times Cited: 13

A short-term wind power prediction approach based on an improved dung beetle optimizer algorithm, variational modal decomposition, and deep learning
Yan He, Wei Wang, Meng Li, et al.
Computers & Electrical Engineering (2024) Vol. 116, pp. 109182-109182
Closed Access | Times Cited: 11

SMGformer: integrating STL and multi-head self-attention in deep learning model for multi-step runoff forecasting
Wenchuan Wang, M. H. Gu, Yang-hao Hong, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6

A novel daily runoff forecasting model based on global features and enhanced local feature interpretation
Dongmei Xu, Yang-hao Hong, Wenchuan Wang, et al.
Journal of Hydrology (2024), pp. 132227-132227
Closed Access | Times Cited: 5

An approach to portfolio optimization with time series forecasting algorithms and machine learning techniques
Jyotirmayee Behera, Pankaj Kumar
Applied Soft Computing (2025), pp. 112741-112741
Closed Access

WaveTransTimesNet: an enhanced deep learning monthly runoff prediction model based on wavelet transform and transformer architecture
Dongmei Xu, Zong Li, Wenchuan Wang, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access

Twin extreme learning machine model and cooperation search algorithm for multi-step-ahead point and interval runoff prediction
Zhong-kai Feng, Pan Liu, Wen-jing Niu, et al.
Journal of Hydrology (2025), pp. 132778-132778
Closed Access

Mixture of experts leveraging informer and LSTM variants for enhanced daily streamflow forecasting
Zerong Rong, Wei Sun, Yutong Xie, et al.
Journal of Hydrology (2025), pp. 132737-132737
Closed Access

Improving the accuracy of daily runoff prediction using informer with black kite algorithm, variational mode decomposition, and error correction strategy
Wenchuan Wang, H. Ren, Zong Li, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access

Assessment of hybrid kernel function in extreme support vector regression model for streamflow time series forecasting based on a bayesian estimator decomposition algorithm
Peng Shi, Lei Xu, Simin Qu, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110514-110514
Closed Access

Probabilistic daily runoff forecasting in high-altitude cold regions using a hybrid model combining DBO and transformer variants
Qiying Yu, Wenzhong Li, Yungang Bai, et al.
Journal of Hydrology Regional Studies (2025) Vol. 59, pp. 102311-102311
Closed Access

Error correction method based on deep learning for improving the accuracy of conceptual rainfall-runoff model
Wang Wenchuan, Yanwei Zhao, Dongmei Xu, et al.
Journal of Hydrology (2024), pp. 131992-131992
Closed Access | Times Cited: 4

Comparison of parameter optimization methods for a runoff forecast model based on a support vector machine
Yerong Zhou, Jidong Li, Guangwen Ma, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024) Vol. 135, pp. 103653-103653
Closed Access | Times Cited: 2

Evaluating the impact of improved filter-wrapper input variable selection on Long-term runoff forecasting using local and global climate information
Binlin Yang, Chen Lu, Bin Yi, et al.
Journal of Hydrology (2024), pp. 132034-132034
Closed Access | Times Cited: 2

Prediction of total volatile basic nitrogen (TVB‐N) in fish meal using a metal‐oxide semiconductor electronic nose based on the VMD‐SSA‐LSTM algorithm
Pei Li, Zhaopeng Li, Yangting Hu, et al.
Journal of the Science of Food and Agriculture (2024) Vol. 104, Iss. 13, pp. 7873-7884
Closed Access | Times Cited: 1

Enhanced Air Quality Prediction Using a Coupled DVMD Informer-CNN-LSTM Model Optimized with Dung Beetle Algorithm
Yang Wu, Chonghui Qian, Hengjun Huang
Entropy (2024) Vol. 26, Iss. 7, pp. 534-534
Open Access | Times Cited: 1

A singular spectrum analysis-enhanced BiTCN-selfattention model for runoff prediction
Wenchuan Wang, Feng-rui Ye, Yiyang Wang, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access | Times Cited: 1

Guidance on the construction and selection of relatively simple to complex data-driven models for multi-task streamflow forecasting
Trung Duc Tran, Jongho Kim
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 9, pp. 3657-3675
Closed Access | Times Cited: 1

Enhancing streamflow prediction in the Wujiang River basin: a two-stage decomposition approach with deep learning integration
Ruichao Zhao, Zhiwen Zheng
Journal of Water and Climate Change (2024) Vol. 15, Iss. 11, pp. 5683-5697
Open Access | Times Cited: 1

Study on runoff forecasting and error correction driven by atmosphere–ocean-land dataset
Xinyu Chang, Jun Guo, Yi Liu, et al.
Expert Systems with Applications (2024) Vol. 263, pp. 125744-125744
Closed Access | Times Cited: 1

Prediction of non-stationary daily streamflow series based on ensemble learning: a case study of the Wei River Basin, China
Wei Ma, Xiao Zhang, Jiancang Xie, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access | Times Cited: 1

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