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What is Pruning Algorithm

Handbook of Research on Geoinformatics
A training algorithm that optimizes the number of hidden layer neurons by removing or disabling unnecessary weights or neurons from a large network that is initially constructed to capture the input-output relationship.
Published in Chapter:
Artificial Neural Networks
Xiaojun Yang (Florida State University, USA)
Copyright: © 2009 |Pages: 7
DOI: 10.4018/978-1-59140-995-3.ch016
Abstract
Artificial neural networks are increasingly being used to model complex, nonlinear phenomena. The purpose of this chapter is to review the fundamentals of artificial neural networks and their major applications in geoinformatics. It begins with a discussion on the basic structure of artificial neural networks with the focus on the multilayer perceptron networks given their robustness and popularity. This is followed by a review on the major applications of artificial neural networks in geoinformatics, including pattern recognition and image classification, hydrological modeling, and urban growth prediction. Finally, several areas are identified for further research in order to improve the success of artificial neural networks for problem solving in geoinformatics.
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