Neural Network Model for Predicting the Resistance of Driven Piles

References

• Baik , K. 2002 . Optimum driving method for steel pipe piles in sands . J. Civil Engineering 22 ( 1-C ): 45 – 55 .
   Google Scholar
• Beringen , F. L. 1979 . Results of loading tests on driven piles in sand . Recent Developments in the Design and Construction of Piles. London : 213 – 225 .
   Google Scholar
• Brucy , F. , J. Meunier , and J. F. Nauroy . 1991 . Behavior of pile plug in sandy soils during and after driving . Proc. 23rd Annual Offshore Technology Conf. 1 : 145 – 154 .
   Google Scholar
• Chan , W. T. , Y. K. Chow , and L. F. Liu . 1995. Neural network: a alternative to pile driving formulas. Comp. and Geotechnics 17(2): 135–156.
   Google Scholar
• Cho , C. W. 2003 . The characteristics of the set-up effect of driven piles . J. Korean Geotechnical Society JKGS 19 ( 4 ): 235 – 246 .
   Google Scholar
• Chow , F. C. , R. J. Jardine , F. Brucy , and J. F. Nauroy . 1998 . Effects of time on capacity of pipe piles in dense marine sand . J. Geotechnical and Geoenvironmental Engineering 124 ( 3 ): 254 – 264 .
   Web of Science ®Google Scholar
• Crowther , C. L. 1988 . Load Testing of Deep Foundations. The Planning Design and Conduct of Pile Load Tests . John Wiley & Sons .
   Google Scholar
• De Nicolar , A. and M. F. Randolph . 1997 . The plugging behavior of driven and jacked piles in sand . Geotechnique London, UK , 47 ( 4 ): 841 – 859 .
   Google Scholar
• Goh , A. T. C. 1994 . Seismic liquefaction potential assessed by neural networks . J. Geotech. Engrg. Div., ASCE 120 ( 9 ): 1467 – 1480 .
   Google Scholar
• GRL Associates, Inc. 1996. CAPWAP User Manual .
   Google Scholar
• Klos , J. and A. Tejchman . 1981 . Bearing capacity calculation for pipe piles . International Conference on Soil Mechanics and Foundation Engineering, Stockholm 2 : 751 – 753 .
   Google Scholar
• Kohonen , T. 1988 . Learning vector quantization . Neural Networks 1 ( 1 ): 303 – 320 .
   Google Scholar
• Kraft , L. M. , Jr. 1991 . Performance of axially loaded pipe piles in sand . J. Geotech. Engrg. 117 ( 2 ): 272 – 296 .
   Google Scholar
• Kusiak , A. and H. Lee . 1996 . Neural computing based design of components for cellular manufacturing . International Journal of Production Research 34 ( 7 ): 1777 – 1790 .
   Web of Science ®Google Scholar
• Lee , I. M. and J. H. Lee . 1996 . Prediction of pile bearing capacity using artificial neural networks . Computers and Geotechnics 18 ( 3 ): 189 – 200 .
   Web of Science ®Google Scholar
• Mitchell , J. K. and Z. V. Solymar . 1984 . Time-dependent strength gain in freshly deposited or densified sand . J. Geotechnical Engineering, ASCE 110 ( 11 ): 1159 – 1576 .
   Google Scholar
• Nauroy , J. F. and P. Le Tirant . 1983 . Model tests on piles in calcareous sands . Proc. Conf. on Geotech. Practice in Offshore Engrg. Austine : 356 – 369 .
   Google Scholar
• Rahman , M. S. , J. Wang , W. Deng , and J. P. Carter . 2001 . A neural network model for the uplift capacity of suction caissions . Computers and Geotechnic 28 : 269 – 287 .
   Web of Science ®Google Scholar
• Schmertmann , J. H. 1991 . The mechanical aging of soils . J. Geotechnical Engineering, ASCE 117 ( 9 ): 1288 – 1330 .
   Google Scholar
• Szechy , C. H. 1959 . Tests with tubular piles . AcTa Technica of the Hungarian Academy of Science 24 : 181 – 219 .
   Google Scholar
• Teh , C. I. , K. S. Wong , A. T. C. Goh , and S. Jaritngam . 1997 . Prediction of pile capacity using neural networks . J. Comp. in Civ. Engrg., ASCE 11 ( 2 ): 129 – 138 .
   Web of Science ®Google Scholar