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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:

An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Sadeq Oleiwi Sulaiman, Ravinesh C. Deo, et al.
Journal of Hydrology (2018) Vol. 569, pp. 387-408
Closed Access | Times Cited: 629

Showing 1-25 of 629 citing articles:

A survey on river water quality modelling using artificial intelligence models: 2000–2020
Tiyasha Tiyasha, Tran Minh Tung, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Journal of Hydrology (2020) Vol. 585, pp. 124670-124670
Closed Access | Times Cited: 528
River water quality index prediction and uncertainty analysis: A comparative study of machine learning models
Seyed Babak Haji Seyed Asadollah, Ahmad Sharafati, Davide Motta, et al.
Journal of environmental chemical engineering (2020) Vol. 9, Iss. 1, pp. 104599-104599
Closed Access | Times Cited: 276
Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
Francesco Granata
Agricultural Water Management (2019) Vol. 217, pp. 303-315
Closed Access | Times Cited: 273
An insight into machine learning models era in simulating soil, water bodies and adsorption heavy metals: Review, challenges and solutions
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Chemosphere (2021) Vol. 277, pp. 130126-130126
Closed Access | Times Cited: 264
Groundwater level prediction using machine learning models: A comprehensive review
Tao Hai, Mohammed Majeed Hameed, Haydar Abdulameer Marhoon, et al.
Neurocomputing (2022) Vol. 489, pp. 271-308
Open Access | Times Cited: 260
Groundwater quality forecasting using machine learning algorithms for irrigation purposes
Ali El Bilali, Abdeslam Taleb, Youssef Brouziyne
Agricultural Water Management (2020) Vol. 245, pp. 106625-106625
Closed Access | Times Cited: 238
Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs
Rana Muhammad Adnan, Zhongmin Liang, Salim Heddam, et al.
Journal of Hydrology (2019) Vol. 586, pp. 124371-124371
Closed Access | Times Cited: 231
An efficient optimization approach for designing machine learning models based on genetic algorithm
Khader M. Hamdia, Xiaoying Zhuang, Timon Rabczuk
Neural Computing and Applications (2020) Vol. 33, Iss. 6, pp. 1923-1933
Open Access | Times Cited: 223
Daily streamflow prediction using optimally pruned extreme learning machine
Rana Muhammad Adnan, Zhongmin Liang, Slaviša Trajković, et al.
Journal of Hydrology (2019) Vol. 577, pp. 123981-123981
Closed Access | Times Cited: 222
Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research
Suraj Kumar Bhagat, Tran Minh Tung, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Journal of Cleaner Production (2019) Vol. 250, pp. 119473-119473
Closed Access | Times Cited: 206
Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)
Saber Kouadri, Ahmed Elbeltagi, Abu Reza Md. Towfiqul Islam, et al.
Applied Water Science (2021) Vol. 11, Iss. 12
Open Access | Times Cited: 201
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Sujan Ghimire, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Aitazaz A. Farooque, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 200
A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data
Shuyu Yang, Dawen Yang, Jinsong Chen, et al.
Journal of Hydrology (2020) Vol. 590, pp. 125206-125206
Open Access | Times Cited: 187
Spatiotemporal Modeling for Nonlinear Distributed Thermal Processes Based on KL Decomposition, MLP and LSTM Network
Yajun Fan, Kangkang Xu, Hui Wu, et al.
IEEE Access (2020) Vol. 8, pp. 25111-25121
Open Access | Times Cited: 169
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Rana Muhammad Adnan, Reham R. Mostafa, Özgür Kişi, et al.
Knowledge-Based Systems (2021) Vol. 230, pp. 107379-107379
Closed Access | Times Cited: 169
Machine learning predictive model based on national data for fatal accidents of construction workers
Jongko Choi, Bonsung Gu, Sangyoon Chin, et al.
Automation in Construction (2019) Vol. 110, pp. 102974-102974
Closed Access | Times Cited: 161
Deep Learning Data-Intelligence Model Based on Adjusted Forecasting Window Scale: Application in Daily Streamflow Simulation
Minglei Fu, Tingchao Fan, Zi’ang Ding, et al.
IEEE Access (2020) Vol. 8, pp. 32632-32651
Open Access | Times Cited: 161
A Machine Learning Ensemble Approach Based on Random Forest and Radial Basis Function Neural Network for Risk Evaluation of Regional Flood Disaster: A Case Study of the Yangtze River Delta, China
Junfei Chen, Qian Li, Huimin Wang, et al.
International Journal of Environmental Research and Public Health (2019) Vol. 17, Iss. 1, pp. 49-49
Open Access | Times Cited: 157
Real-time probabilistic forecasting of river water quality under data missing situation: Deep learning plus post-processing techniques
Yanlai Zhou
Journal of Hydrology (2020) Vol. 589, pp. 125164-125164
Open Access | Times Cited: 152
Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation
Zainab Abdulelah Al-Sudani, Sinan Q. Salih, Ahmad Sharafati, et al.
Journal of Hydrology (2019) Vol. 573, pp. 1-12
Closed Access | Times Cited: 148
Forecasting of water level in multiple temperate lakes using machine learning models
Senlin Zhu, Bahrudin Hrnjica, Mariusz Ptak, et al.
Journal of Hydrology (2020) Vol. 585, pp. 124819-124819
Closed Access | Times Cited: 146
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
A. A. Masrur Ahmed, Ravinesh C. Deo, Qi Feng, et al.
Journal of Hydrology (2021) Vol. 599, pp. 126350-126350
Closed Access | Times Cited: 115
The viability of extended marine predators algorithm-based artificial neural networks for streamflow prediction
Rana Muhammad Adnan Ikram, Ahmed A. Ewees, Kulwinder Singh Parmar, et al.
Applied Soft Computing (2022) Vol. 131, pp. 109739-109739
Closed Access | Times Cited: 113
Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study
Francesco Granata, Fabio Di Nunno, Giovanni de Marinis
Journal of Hydrology (2022) Vol. 613, pp. 128431-128431
Closed Access | Times Cited: 108
The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management
Vijendra Kumar, Hazi Mohammad Azamathulla, Kul Vaibhav Sharma, et al.
Sustainability (2023) Vol. 15, Iss. 13, pp. 10543-10543
Open Access | Times Cited: 105
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