Drought forecasting by ANN, ANFIS, and SVM and comparison of the models
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Natural disaster analysis based on ML and FL using ANN, SVM, EC, and neuro-fuzzy has been performed.
“and CO2 emission [[194], [195], [196]] and natural disaster (e.g. Ref. [197,198], based on ML and FL using ANN, SVM, EC, and neuro-fuzzy.”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [197]
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- Authors
- Mokhtarzad, M., Eskandari, F., Jamshidi Vanjani, N., & Arabasadi, A.
- Affiliations
- Allameh Tabataba'i University (IR)
- Shahid Beheshti University (IR)
- Corresponding author
- Mokhtarzad, Maryam
- Venue
- Environmental Earth Sciences
- Published
- 2017-10-28
- Volume
- 76
- Issue
- 21
- ISSN
- 1866-6280 (ISSN-L)
- 1866-6299
- OpenAlex
- W2765106898
- Cited by
- 203
- References
- 45
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 31 · 2023: 34 · 2022: 41 · 2021: 26 · 2020: 20 · 2019: 11 · 2018: 4
- FWCI
- 6.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Environmental Earth Sciences (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
- Physical Sciences › Environmental Science › Environmental Engineering › Hydrological Forecasting Using AI
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Keywords
- drought forecasting, Standardized Precipitation Index, artificial neural networks, adaptive neuro-fuzzy inference system, support vector machine, model comparison, weather station data, precipitation, Bojnurd
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