One to twelve-month-ahead forecasting of MODIS-derived Qinghai Lake area, using neuro-fuzzy system hybridized by firefly optimization
Author:
Funder
Bu-Ali Sina University Deputy of Research and Technology
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11356-024-32620-7.pdf
Reference77 articles.
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2. Aghelpour P, Mohammadi B, Biazar SM, Kisi O, Sourmirinezhad Z (2020b) A theoretical approach for forecasting different types of drought simultaneously, using entropy theory and machine-learning methods. ISPRS Int J Geo Inf 9(12):701
3. Aghelpour P, Bahrami-Pichaghchi H, Varshavian V (2021) Hydrological drought forecasting using multi-scalar streamflow drought index, stochastic models and machine learning approaches, in northern Iran. Stoch Environ Res Risk Assess 35:1–21
4. Aghelpour P, Kisi O, Varshavian V (2021) Multivariate drought forecasting in short- and long-term horizons using MSPI and data-driven approaches. J Hydrol Eng 26(4):04021006. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002059
5. Aghelpour P, Singh VP, Varshavian V (2021c) Time series prediction of seasonal precipitation in Iran, using data-driven models: a comparison under different climatic conditions. Arab J Geosci 14:1–14
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