Geotechnical parameter prediction from large data sets

  • Authors:
  • I. Davey-Wilson

  • Affiliations:
  • School of Computing and Mathematical Sciences, Oxford Brookes University, Oxford, England

  • Venue:
  • ICAAISE '01 Proceedings of the eighth international conference on The application of artificial intelligence to civil and structural engineering computing
  • Year:
  • 2001

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Abstract

Geotechnical laboratory testing of soils produce two main categories of results: soil identification parameters and soil behaviour parameters. The behaviour parameters will be similar for similar types of soil. From a large database of geotechnical test results it is likely that a knowledge of the soil identification parameters will imply a certain range of behaviour parameters for a similar soil. Numerous geotechnical laboratory test results have been reported in the literature or are held at testing laboratories and could be used for database population and analysis. The aim of this work was to develop a computer system to estimate unknown soil parameters from known test results. The system incorporates an inference mechanism based on similarity functions.