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[Goh Tiong Hwee]

I have place the following paper in the neuroprose archive.

Hardcopy request by snailmail to me at the institute.

Thanks to Steve Pollack for availing the archive service.

Neural Networks And Genetic Algorithm For Economic Forecasting
               Francis Wong, PanYong Tan
              Institute of Systems Science
            National University of Singapore


Abstract:
This paper describes the application of an enhanced neural network and genetic
algorithm to economic forecasting. Our proposed approach has several
significant advantages over conventional forecasting methods such as regression
and the Box-Jenkins methods. Apart from being simple and fast in learning, a
major advantage is that no assumption need to be made about the underlying
function or model, since the neural networks is able to extract hidden
information from the historical data. In addition, the enhanced neural network
offers selective activation and training of neurons based on the instantaneous
causal relationship between the current set of input training data and the
output target. This causal relationship is represented by the Accumulated Input
Error (AIE) indices, which are computed based on the accumulated errors
back-propagated to the input layers during training. The AIE indices are used
in the selection of neurons for activation and training. Training time can be
reduced significantly, especially for large networks designed to capture
temporal information. Although neural networks represent a promising
alternative for forecasting, the problem of network design remains a bottleneck
that could impair widespread applications in practice. The genetic algorithm is
used to evolved optimal neural network architectures automatically, thus
eliminating the many pitfalls associated with human-engineering approaches. The proposed concepts and design paradigm were tested on serveral real applications ( Please email thgoh at iss.nus.sg for a copy of the software ), including the forecast of GDP, air passenger arrival and currency exchage rates.

ftp Instructions:

unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
Name: anonymous
Password: neuron
ftp> cd pub/neuroprose
ftp> binary
ftp> get wong.nnga.ps.Z   
ftp> quit
__________________________________________________________
Tiong Hwee Goh
Institute of Systems Science
National University of Singapore
Heng Mui Keng Terrace
Kent Ridge
Singapore 0511.
Telephone:(65)7726214
Fax      :(65)7782571