Papers20100623115423 < AI_GEOSTATS

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*Title:* Investigation of Two Neural Network Methods in an Automatic Mapping Exercise

*Date:* 1 July 2005

<strong>Authors: </strong>Sridhar Dutta, Rajive Ganguli, Biswajit Samanta

<strong>Link: </strong> <a target="_blank" href="http://publications.epress.monash.edu/doi/pdf/10.2104/ag050020">http://publications.epress.monash.edu/doi/pdf/10.2104/ag050020</a>

*Abstract:*

This paper investigates the performance of two neural network (NN) methods viz. a radial basis function network (RBFN) and a multilayer feed forward network (MFFN) to predict the radioactivity levels at a given test site. A comparative evaluation of the two networks is done using Root mean square error (RMSE), Pearson's r, Mean error (ME) and Mean Absolute error (MAE). It was found that the RBFN performed marginally better compared to the other method.

Reference:

Applied GIS<br />Volume 1, No. 2, August 2005 <br />DOI: 10.2104/ag050020

Topic revision: r3 - 2010-08-13 - 21:16:07 - TheresiaFreska

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