Apr 17, 2020 · We show that a neural network can learn a surrogate model effectively and efficiently and thus can be used as a surrogate simulation model.
Numerical simulation models are usually computation expensive and require expert knowledge. We consider the problem of hydrological modelling and simulation.
We consider the problem of hydrological modelling and simulation. With a training set consisting of pairs of inputs and outputs from an off-the-shelves ...
We consider the problem of hydrological modelling and simulation. With a training set consisting of pairs of inputs and outputs from an off-the-shelves ...
It is argued that the neural network model, although trained on some example terrains, is generally capable of simulating terrains of different sizes and ...
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Hydrological Process Surrogate Modelling and Simulation with Neural Networks ... Authors: Ruixi Zhang; Remmy Zen; Jifang Xing; Dewa Made Sri Arsa; Abhishek Saha ...
This study proposes a deep autoregressive neural network based surrogate method for distributed land surface hydrological modelling. This method converts the ...
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Hydrological Process Surrogate Modelling and Simulation with Neural Networks. Published on Oct 14, 202018 Views. Ruixi Zhang · PAKDD 2020 - Singapore.
Feb 20, 2024 · This research combines the latest developments in surrogate modelling and physics-informed machine learning to propose a novel Physics-Informed Neural Network- ...