| Reference Type | Journal (article/letter/editorial) |
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| Title | A hybrid numerical–probabilistic approach for machine learning-based prediction of liquefaction-induced settlement using CPT data |
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| Journal | Arabian Journal of Geosciences |
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| Authors | Gupta, Tanmay | Author |
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| Ramana, G V | Author |
| Elgamal, Ahmed | Author |
| Year | 2023 (June) | Volume | 16 |
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| Issue | 6 |
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| Publisher | Springer Science and Business Media LLC |
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| DOI | doi:10.1007/s12517-023-11500-3Search in ResearchGate |
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| Generate Citation Formats |
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| Mindat Ref. ID | 15867686 | Long-form Identifier | mindat:1:5:15867686:1 |
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| GUID | 0 |
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| Full Reference | Gupta, Tanmay, Ramana, G V, Elgamal, Ahmed (2023) A hybrid numerical–probabilistic approach for machine learning-based prediction of liquefaction-induced settlement using CPT data. Arabian Journal of Geosciences, 16 (6) doi:10.1007/s12517-023-11500-3 |
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| Plain Text | Gupta, Tanmay, Ramana, G V, Elgamal, Ahmed (2023) A hybrid numerical–probabilistic approach for machine learning-based prediction of liquefaction-induced settlement using CPT data. Arabian Journal of Geosciences, 16 (6) doi:10.1007/s12517-023-11500-3 |
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| In | (2023, June) Arabian Journal of Geosciences Vol. 16 (6) Springer Science and Business Media LLC |
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