Advertisement

Artificial Intelligence in Soil Exploration

  • Kingsley Harrop-Williams
Conference paper

Abstract

Recognizing the inherent randomness of the soil, this paper develops a statistical pattern recognition scheme to optimally identify soil types when the cone penetrometer is used. The system recursively sharpens its memory and includes a fuzzy updating procedure for suspected anomalies. The final result is an artificially intelligent system to aid the soil explorer.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Blockley, D.I. (1975) “Predicting the Likelihood of Structural Accidents,” Proc. Inst. of Civil Eng., Pt. 2, Vol. 59, pp. 659–668.CrossRefGoogle Scholar
  2. Shiraishi, W. and Furuta, H. (1983) “Reliability Analysis Based on Fuzzy Probability,” J. of Eng. Mech. Div., ASCE, Vol. 109, No. EM6, pp. 1445–1459.CrossRefGoogle Scholar
  3. Winterkorn, H.F. and Fang, H. Y. (1975) “Foundation Engineering Handbook,” Van Nostrand Reinhold Co., NY.Google Scholar
  4. Yao, J.T. (1981) “Damage Assessments of Existing Structure,” J. of the Eng. Mech. Div., ASCE, Vol. 106, No. EM4, pp. 785–799.Google Scholar
  5. Zadeh, L.A. (1965) “Fuzzy Sets,” Information and Control, Vol. 8, pp. 338–353.CrossRefzbMATHMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  • Kingsley Harrop-Williams
    • 1
  1. 1.The BDM CorporationMcLeanUSA

Personalised recommendations