Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

Research article (Scientific Reports, 2023) · cited 11× · AI/ML
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Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models

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Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models. Retrieved May 24, 2026, from https://4ort.xyz/entity/feasibility-of-neural-network-metamodels-for-emulation-and-sensitivity-analysis-of-radionuclide-transport-models
MLA “Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/feasibility-of-neural-network-metamodels-for-emulation-and-sensitivity-analysis-of-radionuclide-transport-models.
BibTeX @misc{4ortxyz_feasibility-of-neural-network-metamodels-for-emulation-and-sensitivity-analysis-of-radionuclide-transport-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Feasibility of neural network metamodels for emulation and sensitivity analysis of radionuclide transport models}}, year = {2026}, url = {https://4ort.xyz/entity/feasibility-of-neural-network-metamodels-for-emulation-and-sensitivity-analysis-of-radionuclide-transport-models}, note = {Accessed: 2026-05-24}}
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