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From: karunani@handel.cs.colostate.edu (n karunanithi)
Newsgroups: comp.ai.neural-nets
Subject: References for NN as a predictor
Message-ID: <10472@ccncsu.ColoState.EDU>
Date: 21 Oct 90 02:34:03 GMT
Sender: news@ccncsu.ColoState.EDU
Reply-To: karunani@handel.cs.colostate.edu (n karunanithi)
Organization: Dept. of Computer Science, Colorado State University.
Lines: 56

Dear Connectionists,

   Sometime back I requested you all to help me in locating references
   for predicting future events using NN.
   I got a few reponses. I thank the following people for their help.


1. Denis Anthony at Computing Services, Warwick University, UK.

2. P.Havener at Eastman Kodak, Texas:

 Bhat and McAvoy, University of Maryland Dept. of Chemical Engineering,
 College Park Maryland, 20742 "Use of Neural Nets for Dynamic Modeling
 and Control of Chemical Process Systems" -- In this paper the future PH
 of a stired tank reactor was predicted by training a net using past
 historical data on intputs and outputs, to the tank. -- very good work,
 the concepts can be implemented in a standard M&R back-prop, feed
 forward nets.

 Weigend, Huberman and Rumelhart, "Predicting the Future: A
 Connectionist Approach", Stanford PDP Research Group,
 Stanford-PDP-90-01, PARC-SSL-90-20, similar to McAvoy's work.

 Jeffery Elman. "Finding Structure in Time", Center for Research in
 Language, University of California, San Diego. CRL technical report
 8801. - recurrent neural net that does not require multiple inputs
 over time.

3.  R.B Patil:
R. Sharda, and R.B. Patil, ``Neural Networks as
Forecasting Experts: An Empirical Test,"
Proc. IJCNN, Washington D.C , 1990 June, Vol.II, pp 491-494.

4. And few other references that I came accross:


J. Moody,``Fast Learning In Multi-Resolution hierarchies,"
Advances in Neural Information Processing Systems 1., Edited by David
S. Touretzky, Morgan Kaufman Publishers, Inc. 1989, pp 29-39.

R. Shadmehr, and D.Z.D'Argenio, ``A Comparison of a Neural
Network Based Estimator and Two Statistical Estimators in a Sparse and Noisy 
Data Environment,"
Proc. IJCNN, Washington D.C , 1990 June, Vol.I, pp 289-292.

P. Werbos, ``Generalization of Backpropagation with 
Application to Recurrent Gas Market Model,"
Neural Networks, 1988, Vol. 1, pp 339-356.


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N Karunanithi                         karunani@handel.cs.colostate.edu
Computer Science Dept,
Colorado State University,
Ft Collins, CO - 80523.
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