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THE USE OF ARTIFICIAL NEURAL NETWORKS TO PREDICT GROUND MOVEMENTS CAUSED BY TUNNELING (2009)
During the design phase of a tunnel, one of the concerns of tunnel engineers is estimating ground movements induced by tunneling, in order to take steps to prevent or minimize possible damage caused by these movements, to adjacent structures. In this work, an estimate is made of displacements in the ground brought on by tunnel excavation by using an artificial intelligence technique called Artificial Neural Networks (ANN). The computer tool utilized was the MatLab program and the networks were of the feedforward type, with the Resilient Backpropagation (trainrp) learning algorithm.
Reference:
Geotechnical Aspects of Underground Construction in Soft Ground – Ng, Huang & Liu (eds), © 2009 Taylor & Francis Group, London
Geotechnical Aspects of Underground Construction in Soft Ground – Ng, Huang & Liu (eds), © 2009 Taylor & Francis Group, London
Organization:
University of Brasilia, Brazil
Brazil
University of Brasilia, Brazil
Brazil
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