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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.

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Showing 21 citing articles:

Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft computing techniques
Charuni I. Madhushani, K. G. S. Dananjaya, I.U. Ekanayake, et al.
Journal of Hydrology (2024) Vol. 631, pp. 130846-130846
Closed Access | Times Cited: 24
Research on Water Resource Modeling Based on Machine Learning Technologies
Liu Ze, Jingzhao Zhou, Xiaoyang Yang, et al.
Water (2024) Vol. 16, Iss. 3, pp. 472-472
Open Access | Times Cited: 21
A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI
U.A.K.K. Perera, D.T.S. Coralage, I.U. Ekanayake, et al.
Results in Engineering (2024) Vol. 21, pp. 101920-101920
Open Access | Times Cited: 17
Daily Streamflow Forecasting in Mountainous Catchment Using XGBoost, LightGBM and CatBoost
Robert Szczepanek
Hydrology (2022) Vol. 9, Iss. 12, pp. 226-226
Open Access | Times Cited: 64
Comparative Study for Daily Streamflow Simulation with Different Machine Learning Methods
Ruonan Hao, Zhixu Bai
Water (2023) Vol. 15, Iss. 6, pp. 1179-1179
Open Access | Times Cited: 24
Prediction method for the dynamic response of expressway lateritic soil subgrades on the basis of Bayesian optimization CatBoost
Xuanjia Huang, Weizheng Liu, Qing Guo, et al.
Soil Dynamics and Earthquake Engineering (2024) Vol. 186, pp. 108943-108943
Closed Access | Times Cited: 8
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: 6
Interpretable probabilistic modeling method for runoff prediction: A case study in Yangtze River basin, China
Qin Shen, Mo Li, Guanjun Liu, et al.
Journal of Hydrology Regional Studies (2024) Vol. 52, pp. 101684-101684
Open Access | Times Cited: 5
Exploring the potential of deep learning for streamflow forecasting: A comparative study with hydrological models for seasonal and perennial rivers
Ardalan Izadi, Nastaran Zarei, Mohammad Reza Nikoo, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124139-124139
Closed Access | Times Cited: 5
Integrated forecasting of monthly runoff considering the combined effects of teleconnection factors
Jianbo Chang, Baowei Yan, Mingbo Sun, et al.
Journal of Hydrology Regional Studies (2025) Vol. 58, pp. 102206-102206
Closed Access
Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input
Jinqiang Wang, Zhanjie Li, Ling Zhou, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 967-967
Open Access
An efficient parallel runoff forecasting model for capturing global and local feature information
Yang-hao Hong, Dongmei Xu, Wenchuan Wang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Research on the Nonlinear and Interactive Effects of Multidimensional Influencing Factors on Urban Innovation Cooperation: A Method Based on an Explainable Machine Learning Model
Rui Wang, Xingping Wang, Zhonghu Zhang, et al.
Systems (2025) Vol. 13, Iss. 3, pp. 187-187
Open Access
Investigating the potential of EMA-embedded feature selection method for ESVR and LSTM to enhance the robustness of monthly streamflow forecasting from local meteorological information
Lei Xu, Peng Shi, Hongshi Wu, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131230-131230
Closed Access | Times Cited: 3
Spatiotemporal evolution of ecosystem health and its driving factors in the southwestern karst regions of China
Ninglei Ouyang, Xiaoping Rui, Xuepeng Zhang, et al.
Ecological Indicators (2024) Vol. 166, pp. 112530-112530
Open Access | Times Cited: 3
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
An evaluation of random forest based input variable selection methods for one month ahead streamflow forecasting
Wei Fang, Kun Ren, Tie-Jun Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Enhanced streamflow prediction using SWAT’s influential parameters: a comparative analysis of PCA-MLR and XGBoost models
R. Yamini Priya, R. Manjula
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 4053-4076
Closed Access | Times Cited: 4
Machine Learning to Characterize Biogenic Isoprene Emissions and Atmospheric Formaldehyde with Their Environmental Drivers in the Marine Boundary Layer
Tianyu Wang, Shanshan Wang, Ruibin Xue, et al.
Atmosphere (2024) Vol. 15, Iss. 6, pp. 679-679
Open Access
Combining traditional hydrological models and machine learning for streamflow prediction
Antônio Duarte Marcos, Cleiton da Silva Silveira, José Micael Ferreira da Costa, et al.
RBRH (2024) Vol. 29
Open Access
Hierarchical Temporal Scale Framework for Real-Time Streamflow Prediction in Reservoir-Regulated Basins
Jiaxuan Chang, Xuefeng Sang, Junlin Qu, et al.
Research Square (Research Square) (2024)
Open Access
HARNESSING XGBOOST 2.0: A LEAP FORWARD IN CLIMATE SCIENCE ANALYTICS
Miller Tymoteusz, Polina Kozlovska, Adrianna Łobodzińska, et al.
ГРААЛЬ НАУКИ (2023), Iss. 34, pp. 423-431
Open Access
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