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Learning the neuron functions within a neural network via Genetic Programming: Applications to geophysics and hydrogeology

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3 Author(s)
Alan J. Barton ; Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, Ottawa, Ontario, Canada ; Julio J. Valdes ; Robert Orchard

A neural network classifier is sought. Classical neural network neurons are aggregations of a weight multiplied by an input value and then controlled via an activation function. This paper learns everything within the neuron using a variant of genetic programming called gene expression programming. That is, this paper does not explicitly use weights or activation functions within a neuron, nor bias nodes within a layer. Promising preliminary results are reported for a study of the detection of underground caves (a 1 class problem) and for a study of the interaction of water and minerals near a glacier in the Arctic (a 5 class problem).

Published in:

2009 International Joint Conference on Neural Networks

Date of Conference:

14-19 June 2009