An Artificial Neural Network System of Leading Indicators
We construct an artificial neural network to act as a system of leading indicators. We focus on radial basis functions as the architecture and forward selection as the method for determining the number of basis functions in the network. A brief review is given of the advantages of this as a strategy. Using common heuristics to determine scaling, radii and centre population, we find that the results for output growth prediction for six European countries are promising.
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|Date of creation:||Jan 1999|
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