Using Artificial Neural Networks for Knowledge Discovery of River Pollution and Land Use Impacts

2011 ◽  
Vol 8 (11) ◽  
pp. 111-118
Author(s):  
Anita Talib ◽  
Noresah Mohd Shariff ◽  
Yahya Abu Hasan
Keyword(s):  
Neural Networks ◽  
Land Use ◽  
Artificial Neural Networks ◽  
Knowledge Discovery ◽  
River Pollution ◽  
Land Use Impacts ◽  
Artificial Neural

scholarly journals Inferring Landscape-Scale Land-Use Impacts on Rivers Using Data from Mesocosm Experiments and Artificial Neural Networks

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0120901 ◽  
Author(s):  
Regina H. Magierowski ◽  
Steve M. Read ◽  
Steven J. B. Carter ◽  
Danielle M. Warfe ◽  
Laurie S. Cook ◽  
...  
Keyword(s):  
Neural Networks ◽  
Land Use ◽  
Artificial Neural Networks ◽  
Landscape Scale ◽  
Land Use Impacts ◽  
Mesocosm Experiments ◽  
Artificial Neural ◽  
Using Data

Knowledge Discovery with Artificial Neural Networks

2011 ◽  
pp. 669-673
Author(s):  
Juan R. Rabuñal Dopico ◽  
Daniel Rivero Cebrian ◽  
Julián Dorado de la Calle ◽  
Nieves Pedreira Souto
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Knowledge Discovery ◽  
Powerful Technique ◽  
Complex Problems ◽  
New Information ◽  
Wide Range ◽  
The World ◽  
Artificial Neural

The world of Data Mining (Cios, Pedrycz & Swiniarrski, 1998) is in constant expansion. New information is obtained from databases thanks to a wide range of techniques, which are all applicable to a determined set of domains and count with a series of advantages and inconveniences. The Artificial Neural Networks (ANNs) technique (Haykin, 1999; McCulloch & Pitts, 1943; Orchad, 1993) allows us to resolve complex problems in many disciplines (classification, clustering, regression, etc.), and presents a series of advantages that convert it into a very powerful technique that is easily adapted to any environment. The main inconvenience of ANNs, however, is that they can not explain what they learn and what reasoning was followed to obtain the outputs. This implies that they can not be used in many environments in which this reasoning is essential.

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