TR Available: The Use of Cross-Validation in Neural Network Ext

[Christopher Gordon]

FTP-host: archive.cis.ohio-state.edu
FTP-filename: /pub/neuroprose/gordon.extrapolation.ps.Z

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The following 12 page paper is now available by ftp:

The Use of Cross-Validation in Neural Network
Extrapolation of Forest Tree Growth.

C. Gordon, University of the Witwatersrand.

Presented at PRASA (1994).

Abstract:
A back-propagation multilayer Artificial Neural 
Network (ANN) is used to model the mean growth
rate of different plots of Pine trees.
Cross-validation is found to be essential in 
providing a good extrapolation. Predictions are 
made for different plots which have different 
initial densities and different artificial thinning
regimes. Comparisons are made  with a
standard nonlinear regression solution.


* FTP procedure:
 unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
 Name: anonymous
 Password: (email address) 
 ftp> cd pub/neuroprose
 ftp> binary
 ftp> get gordon.extrapolation.ps.Z
 ftp> quit
 unix> uncompress gordon.extrapolation.ps.Z
 unix> lpr gordon.extrapolation.ps  (or however you print postscript)




 ******************************************************************
* Christopher Gordon                                               *
* Department of Applied Maths                                      *  
* University of the Witwatersrand                                  *  
* Internet : CHRIS at gauss.cam.wits.ac.za                                 *
* Snail Mail : PO Box 65684, Benmore 2010, South Africa            *
* Tel: (011)716-3229(W)                                           *
*                                                                  * 
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