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:

Prediction of agricultural drought index in a hot and dry climate using advanced hybrid machine learning
Mohsen Rezaei, Mehdi Azhdary Moghaddam, Gholamreza Azizyan, et al.
Ain Shams Engineering Journal (2024) Vol. 15, Iss. 5, pp. 102686-102686
Open Access | Times Cited: 7

Showing 7 citing articles:

A systematic review of trustworthy artificial intelligence applications in natural disasters
A. S. Albahri, Yahya Layth Khaleel, Mustafa Abdulfattah Habeeb, et al.
Computers & Electrical Engineering (2024) Vol. 118, pp. 109409-109409
Open Access | Times Cited: 33

Beyond Traditional Metrics: Exploring the Potential of Hybrid Algorithms for Drought Characterization and Prediction in the Tromso Region, Norway
Sertaç Oruç, Türker Tuğrul, Mehmet Ali Hınıs
Applied Sciences (2024) Vol. 14, Iss. 17, pp. 7813-7813
Open Access | Times Cited: 3

Evaluating Performances of LSTM, SVM, GPR, and RF for Drought Prediction in Norway: A Wavelet Decomposition Approach on Regional Forecasting
Sertaç Oruç, Mehmet Ali Hınıs, Türker Tuğrul
Water (2024) Vol. 16, Iss. 23, pp. 3465-3465
Open Access | Times Cited: 1

A novel feature extraction-selection technique for long lead time agricultural drought forecasting
Mehdi Mohammadi Ghaleni, Mansour Moradi, Mahnoosh Moghaddasi
Journal of Hydrology (2024), pp. 132332-132332
Closed Access

Development of deep learning approaches for drought forecasting: a comparative study in a cold and semi-arid region
Amin Gharehbaghi, Redvan Ghasemlounıa, Babak Vaheddoost, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access

Drought Prediction Using Advanced Hybrid Machine Learning for Arid and Semi-Arid Environments
Mohsen Rezaei, Mehdi Azhdary Moghaddam, Jamshid Piri, et al.
KSCE Journal of Civil Engineering (2024), pp. 100025-100025
Open Access

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