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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:

Predicting Standardized Streamflow index for hydrological drought using machine learning models
S. Shamshirband, Sajjad Hashemi, Hana Salimi, et al.
Engineering Applications of Computational Fluid Mechanics (2020) Vol. 14, Iss. 1, pp. 339-350
Open Access | Times Cited: 267

Showing 1-25 of 267 citing articles:

Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm
Saeed Samadianfard, Sajjad Hashemi, Katayoun Kargar, et al.
Energy Reports (2020) Vol. 6, pp. 1147-1159
Open Access | Times Cited: 179
Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data
Rana Muhammad Adnan, Reham R. Mostafa, Hongliang Dai, et al.
Engineering Applications of Computational Fluid Mechanics (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 63
A review of recent developments on drought characterization, propagation, and influential factors
Vinícius de Matos Brandão Raposo, Veber Afonso Figueiredo Costa, André Ferreira Rodrigues
The Science of The Total Environment (2023) Vol. 898, pp. 165550-165550
Closed Access | Times Cited: 60
Prediction heavy metals accumulation risk in rice using machine learning and mapping pollution risk
Bing Zhao, Wenxuan Zhu, Shefeng Hao, et al.
Journal of Hazardous Materials (2023) Vol. 448, pp. 130879-130879
Closed Access | Times Cited: 59
Application of machine learning in optical fiber sensors
Yifan Zhou, Yanan Zhang, Qi Yu, et al.
Measurement (2024) Vol. 228, pp. 114391-114391
Closed Access | Times Cited: 16
Streamflow Prediction Using Deep Learning Neural Network: Case Study of Yangtze River
Darong Liu, Wenchao Jiang, Lin Mu, et al.
IEEE Access (2020) Vol. 8, pp. 90069-90086
Open Access | Times Cited: 114
Drought vulnerability and risk assessment in India: Sensitivity analysis and comparison of aggregation techniques
V. Sahana, Arpita Mondal, Parvathi Sreekumar
Journal of Environmental Management (2021) Vol. 299, pp. 113689-113689
Open Access | Times Cited: 75
Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm
Sedigheh Mohamadi, Saad Sh. Sammen, Fatemeh Panahi, et al.
Natural Hazards (2020) Vol. 104, Iss. 1, pp. 537-579
Closed Access | Times Cited: 73
Prediction of Yangtze River streamflow based on deep learning neural network with El Niño–Southern Oscillation
Si Ha, Darong Liu, Lin Mu
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 73
Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach
Rana Muhammad Adnan, Andrea Petroselli‬, Salim Heddam, et al.
Natural Hazards (2021) Vol. 105, Iss. 3, pp. 2987-3011
Closed Access | Times Cited: 69
Groundwater level prediction in arid areas using wavelet analysis and Gaussian process regression
Shahab S. Band, Essam Heggy, Sayed M. Bateni, et al.
Engineering Applications of Computational Fluid Mechanics (2021) Vol. 15, Iss. 1, pp. 1147-1158
Open Access | Times Cited: 68
Implementing a novel deep learning technique for rainfall forecasting via climatic variables: An approach via hierarchical clustering analysis
Shah Fahad, Fang Su, Sufyan Ullah Khan, et al.
The Science of The Total Environment (2022) Vol. 854, pp. 158760-158760
Closed Access | Times Cited: 64
Predicting the number of dusty days around the desert wetlands in southeastern Iran using feature selection and machine learning techniques
Zohre Ebrahimi‐Khusfi, Ali Reza Nafarzadegan, Fatemeh Dargahian
Ecological Indicators (2021) Vol. 125, pp. 107499-107499
Open Access | Times Cited: 63
Meteorological and hydrological droughts in Mekong River Basin and surrounding areas under climate change
Yishan Li, Hui Lü, Kun Yang, et al.
Journal of Hydrology Regional Studies (2021) Vol. 36, pp. 100873-100873
Open Access | Times Cited: 62
Future ecosystem service value modeling with land cover dynamics by using machine learning based Artificial Neural Network model for Jashore city, Bangladesh
Syed Riad Morshed, Md. Abdul Fattah, Md. Nazmul Haque, et al.
Physics and Chemistry of the Earth Parts A/B/C (2021) Vol. 126, pp. 103021-103021
Closed Access | Times Cited: 59
A comparative analysis of data mining techniques for agricultural and hydrological drought prediction in the eastern Mediterranean
Safwan Mohammed, Ahmed Elbeltagi, Bashar Bashir, et al.
Computers and Electronics in Agriculture (2022) Vol. 197, pp. 106925-106925
Open Access | Times Cited: 51
Application of Machine Learning and Process-Based Models for Rainfall-Runoff Simulation in DuPage River Basin, Illinois
Amrit Bhusal, Utsav Parajuli, Sushmita Regmi, et al.
Hydrology (2022) Vol. 9, Iss. 7, pp. 117-117
Open Access | Times Cited: 50
Drought Forecasting: A Review and Assessment of the Hybrid Techniques and Data Pre-Processing
Mustafa A. Alawsi, Salah L. Zubaidi, Nabeel Saleem Saad Al-Bdairi, et al.
Hydrology (2022) Vol. 9, Iss. 7, pp. 115-115
Open Access | Times Cited: 46
Automatic pavement damage predictions using various machine learning algorithms: Evaluation and comparison
Ritha Nyirandayisabye, Huixia Li, Qiming Dong, et al.
Results in Engineering (2022) Vol. 16, pp. 100657-100657
Open Access | Times Cited: 42
Pre- and post-dam river water temperature alteration prediction using advanced machine learning models
Dinesh Kumar Vishwakarma, Rawshan Ali, Shakeel Ahmad Bhat, et al.
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 55, pp. 83321-83346
Open Access | Times Cited: 41
Prediction of Streamflow Drought Index for Short-Term Hydrological Drought in the Semi-Arid Yesilirmak Basin Using Wavelet Transform and Artificial Intelligence Techniques
Okan Mert Katipoğlu
Sustainability (2023) Vol. 15, Iss. 2, pp. 1109-1109
Open Access | Times Cited: 37
Application of Innovative Machine Learning Techniques for Long-Term Rainfall Prediction
Suman Markuna, Pankaj Kumar, Rawshan Ali, et al.
Pure and Applied Geophysics (2023) Vol. 180, Iss. 1, pp. 335-363
Closed Access | Times Cited: 34
Forecasting vapor pressure deficit for agricultural water management using machine learning in semi-arid environments
Ahmed Elbeltagi, Aman Srivastava, Jinsong Deng, et al.
Agricultural Water Management (2023) Vol. 283, pp. 108302-108302
Open Access | Times Cited: 33
A review of deep learning and machine learning techniques for hydrological inflow forecasting
Sarmad Dashti Latif, Ali Najah Ahmed
Environment Development and Sustainability (2023) Vol. 25, Iss. 11, pp. 12189-12216
Closed Access | Times Cited: 30
Future changes in water resources, floods and droughts under the joint impact of climate and land-use changes in the Chao Phraya basin, Thailand
Shuyu Yang, Baoxu Zhao, Dawen Yang, et al.
Journal of Hydrology (2023) Vol. 620, pp. 129454-129454
Open Access | Times Cited: 26
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