[comp.ai.neural-nets] Weather forecasting References

muttiah@stable.ecn.purdue.edu (Ranjan S Muttiah) (10/13/90)

I wish to thank those who responded to my request.

There was one paper by Widrow and Hoff for weather forecasting (using 
madaline ?) in the early 60's that I'm trying to locate.  Anyone know of
this paper ?

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For predicting time series:

Moody, J. Darken, C., 1989, Fast Learning in Networks of Locally-Tuned
Processing Units, Neural Computation, 1(2), pp. 281-294

For predicting weather:

Rogers, D., 1990, Predicting Weather Using a Genetic Memory: A
Combination of Kanerva's Sparse Distributed Memory with Holland's
Genetic Algorithms, Advances in Neural Information Processing Systems,
vol 2, pp. 455-464

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One paper I have found particularly interesting is 

Predicting the future: A Connectionist Approach
A.S Weigend, B.A Huberman and D.E Rumelhart, 1990
Stanford Universtity technical report Standford-PDP-90-01
Submitted to the International Journal of Neural Systems.

in which the authors describe their work in perdicting future values 
of chaotic time series using backprop networks. It is based on a previous
paper:

Nonlinear Signal processing using neural networks: prediction and
system modelling.
A.S Lapedes and R.M Farber
Technical report LA-UR-87-2662
Los Alamos National Laboratory, 1987

aboulang@bbn.com (Albert Boulanger) (10/14/90)

In article <1990Oct13.042132.27956@ecn.purdue.edu> muttiah@stable.ecn.purdue.edu (Ranjan S Muttiah) writes:

--

   One paper I have found particularly interesting is 

   Predicting the future: A Connectionist Approach
   A.S Weigend, B.A Huberman and D.E Rumelhart, 1990
   Stanford Universtity technical report Standford-PDP-90-01
   Submitted to the International Journal of Neural Systems.


One other excellent paper that represents this approach (chaotic time
series prediction) is:

"Nonlinear Forcasting as a Way of Distinguishing Chaos from Measurement
Error in Time Series"
George Sugihara & Robert M. May
Nature, Vol344, 19 April 1990, 734-741

They give examples where the nonlinear perdiction technique works AND
(contrary to what one sees in the AI world) does not work.

Regards,
Albert Boulanger
aboulanger@bbn.com