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Naila Matin

affiliation not provided to SSRN

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Scholarly Papers (1)

1.

Hydrologically constrained genetic programming for interpretable rainfall--runoff model discovery: A process-informed machine learning approach

Number of pages: 49 Posted: 09 Apr 2026
affiliation not provided to SSRN, The University of Sydney - School of Civil Engineering, Delft University of Technology, Macquarie University and National University of Singapore (NUS)
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Abstract:

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genetic programming, rainfall-runoff modelling, process-informed machine learning, conceptual hydrological models, model structure discovery