Grammatical inference techniques and their application in ground investigation

MORREY, I., ORAM, A., COOPER, D., ROGERS, D and STEPHENSON, P. (2008). Grammatical inference techniques and their application in ground investigation. Computer-aided civil and infrastructure engineering, 23 (1), 17-30.

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Link to published version:: https://doi.org/10.1111/j.1467-8667.2007.00517.x

Abstract

Ground investigations often use trial pits and borehole cores on construction sites to determine the strata likely to be encountered at various depths. The data obtained from trial pits can be coded into a form that can be used as sample observations for input to a grammatical inference machine. A grammatical inference machine is a black box, which when presented with a sample of observations of some unknown source language, produces a grammar which is compatible with the sample. This article presents a heuristic model for a grammatical inference machine, which takes as data sentences and non-sentences identified as such, and is capable of inferring grammars in the class of context-free grammars expressed in Chomsky Normal Form. An algorithm and its corresponding software implementation have been developed based on this model. The software takes, as input, coded representations of ground investigation data, and produces as output a grammar which describes and classifies the geotechnical data observed in the area, and also promises the possibility of being able to predict the likely configuration of strata across the site.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.1111/j.1467-8667.2007.00517.x
Page Range: 17-30
Depositing User: Ann Betterton
Date Deposited: 17 Nov 2010 14:36
Last Modified: 18 Mar 2021 21:00
URI: https://shura.shu.ac.uk/id/eprint/2654

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