[PDF][PDF] Rainfall-runoff modelling using artificial neural networks (ANNs): modelling and understanding

AM Kalteh - 2008 - sid.ir
In recent years, ARTIFICIAL NEURAL NETWORKS (ANNs) have become one of the most
promising tools in order to model complex hydrological processes such as the rainfall-runoff …

[HTML][HTML] A probabilistic method for assisting knowledge extraction from artificial neural networks used for hydrological prediction

GB Kingston, HR Maier, MF Lambert - Mathematical and Computer …, 2006 - Elsevier
Knowledge extraction from artificial neural network weights is a developing and increasingly
active field. In the attempt to overcome the 'black-box'reputation, numerous methods have …

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

CW Dawson, NJ Mount, RJ Abrahart… - Journal of …, 2014 - iwaponline.com
This paper addresses the difficult question of how to perform meaningful comparisons
between neural network-based hydrological models and alternative modelling approaches …

Legitimising data-driven models: exemplification of a new data-driven mechanistic modelling framework

NJ Mount, CW Dawson… - Hydrology and Earth …, 2013 - hess.copernicus.org
In this paper the difficult problem of how to legitimise data-driven hydrological models is
addressed using an example of a simple artificial neural network modelling problem. Many …

應用類神經網路於模擬皮克林乳液製備方法之研究

劉彥甫 - 2013 - airitilibrary.com
皮克林(Pickering) 乳液為水相與油相添加固體粒子所製備而成的乳化系統,
而利用固體粒子與界面活性劑協同的方法可以使乳液更加的穩定. 此實驗方法中所影響乳液油滴 …

[引用][C] Development of stochastic Artificial Neural Networks for hydrological prediction

GB Kingstone, MF Lambert, HR Maier - Center for Applied Modeling in Water …, 2004