Time Series Prediction of Chimney Foundation Settlement by Neural Networks
Publication: International Journal of Geomechanics
Volume 11, Issue 3
Abstract
Neural network (NN) models for time series forecasting were initially used in economic fields. In this paper, NN models for time series forecasting are introduced for use in forecasting the settlement of chimney foundations. The data sets used in the NN models were measured in the field. Seven models with different input series are developed to determine the optimal structure of the network. In evaluating the network performance, the network model that uses the previous nine months’ settlement values as input is selected as the optimal model. The analysis results demonstrate that the settlement values predicted by the optimal model are in good agreement with the field measurements. In addition, as the number of data points in the input series increases, the NN performance clearly improves, and this improvement stops after the input series has increased to a certain extent. This demonstrates that the time-series-based NN model can also be successfully applied to predict foundation settlement.
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Information & Authors
Information
Published In
International Journal of Geomechanics
Volume 11 • Issue 3 • June 2011
Pages: 154 - 158
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Aug 10, 2009
Accepted: Aug 23, 2010
Published online: May 16, 2011
Published in print: Jun 1, 2011
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