Eine praktische Methode für die Vorhersage von Sohlwassereinbrüchen unter Verwendung eines Hybridmodells aus künstlicher Intelligenz und GIS
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Geotechnical Engineering and Engineering Geology,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s10230-023-00932-8.pdf
Reference34 articles.
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3. Egbueri JC, Agbasi JC (2022a) Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms. Environ Sci Pollut R 29(25):38346–38373
4. Egbueri JC, Agbasi JC (2022b) Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria. Environ Sci Pollut R 29(38):57147–57171
5. Egbueri JC, Agbasi JC (2022) Performances of MLR, RBF-NN, and MLP-NN in the evaluation and prediction of water resources quality for irrigation purposes under two modeling scenarios. Geocarto Int. https://doi.org/10.1080/10106049.2022.2087758
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