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Accuracy, uncertainty, and interpretability assessments of ANFIS models to predict dust concentration in semi-arid regions.
Environ Sci Pollut Res Int. 2021 Feb;28(6):6796-6810. doi: 10.1007/s11356-020-10957-z. Epub 2020 Oct 3.
Environ Sci Pollut Res Int. 2021.
PMID: 33011943
Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers.
Ebrahimi-Khusfi Z, Nafarzadegan AR, Khosroshahi M.
Ebrahimi-Khusfi Z, et al. Among authors: nafarzadegan ar.
Environ Monit Assess. 2021 Jun 22;193(7):437. doi: 10.1007/s10661-021-09198-5.
Environ Monit Assess. 2021.
PMID: 34159451
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Predicting the dust events frequency around a degraded ecosystem and determining the contribution of their controlling factors using gradient boosting-based approaches and game theory.
Ebrahimi-Khusfi Z, Dargahian F, Nafarzadegan AR.
Ebrahimi-Khusfi Z, et al. Among authors: nafarzadegan ar.
Environ Sci Pollut Res Int. 2022 May;29(24):36655-36673. doi: 10.1007/s11356-021-17265-0. Epub 2022 Jan 22.
Environ Sci Pollut Res Int. 2022.
PMID: 35064502
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Monitoring the water surface of wetlands in Iran and their relationship with air pollution in nearby cities.
Ebrahimi-Khusfi Z, Nafarzadegan AR, Ebrahimi-Khusfi M, Zandifar S.
Ebrahimi-Khusfi Z, et al. Among authors: nafarzadegan ar.
Environ Monit Assess. 2022 Jun 8;194(7):488. doi: 10.1007/s10661-022-10144-2.
Environ Monit Assess. 2022.
PMID: 35674846
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