Artificial intelligence and machine learning for disaster prediction: a scientometric analysis of highly cited papers
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11069-024-06616-y.pdf
Reference30 articles.
1. Barnes B, Dunn S, Wilkinson S (2019) Natural hazards, disaster management and simulation: a bibliometric analysis of keyword searches. Nat Hazards 97:813–840. https://doi.org/10.1007/s11069-019-03677-2
2. Chamola V, Hassija V, Gupta S et al (2021) Disaster and pandemic management using mMachine learning: a survey. IEEE Internet Things J 8:16047–16071. https://doi.org/10.1109/JIOT.2020.3044966
3. Dandagala S, Reddy MS, Murthy DS, Nagaraj G (2017) Artificial neural networks applications in groundwater hydrology—A review. Artif Intell Syst Mach Learn 9:182–187
4. Dodangeh E, Choubin B, Eigdir AN et al (2020) Integrated machine learning methods with resampling algorithms for flood susceptibility prediction. Sci Total Environ 705:135983. https://doi.org/10.1016/j.scitotenv.2019.135983
5. Ezugwu AE, Greeff J, Ho Y-S (2023) A comprehensive study of groundbreaking machine learning research: analyzing highly cited and impactful publications across six decades. J Eng Res. https://doi.org/10.1016/j.jer.2023.10.027
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