Sensitivity analysis for comparison, validation and physical legitimacy of neural network-based hydrological models

This paper addresses the difficult question of how to perform meaningful comparisons between neural network-based hydrological models and alternative modelling approaches. Standard, goodness-of-fit metric approaches are limited since they only assess numerical performance and not physical legitimacy...

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Bibliographic Details
Main Authors: Christian Dawson, Nick J. Mount, Robert J. Abrahart, J. Louis
Format: Default Article
Published: 2014
Subjects:
Other information and computing sciences not elsewhere classified
Generalised linear model
Index flood
Neural network
Partial derivative
Physical legitimacy
Sensitivity analysis
Ungauged catchment
Information and Computing Sciences not elsewhere classified
Online Access:https://hdl.handle.net/2134/14361
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