Forecasting vertical ground surface movement from shrinking/swelling soils with artificial neural networks

International Journal for Numerical and Analytical Methods in Geomechanics

Volumn 32, Issue 10, 2008, Pages 1229-1245

  Doris, Jeffrey J ^a   Rizzo, Donna M ^a   Dewoolkar, Mandar M ^a  

^a University of Vermont ^*  (United States)

Author keywords

Artificial neural networks; Expansive soils; Shrink swell properties

Indexed keywords

ABILITY TESTING; ANCHORAGES (FOUNDATIONS); ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CLIMATOLOGY; ELECTRIC FAULT LOCATION; FINANCIAL DATA PROCESSING; FORECASTING; GROUNDWATER; LIGHTNING; MOISTURE DETERMINATION; OFFSHORE OIL WELL PRODUCTION; SOIL MECHANICS; SOIL MOISTURE; SOILS; SURFACE TESTING; TESTING; TIME SERIES ANALYSIS; UNDERWATER SOILS; WATER CONTENT;

ARTIFICIAL NEURAL NETWORKS; AUSTRALIA; CLIMATE CONDITIONS; CLIMATE DATA; COUNTER PROPAGATION; COUNTER-PROPAGATION NETWORKS; EXPANSIVE SOILS; FIELD MEASUREMENTS; GROUND SURFACE ELEVATION; GROUND SURFACE MOVEMENTS; POST-PROCESSING; RAINFALL DATA; SHRINK-SWELL PROPERTIES; SOIL MOISTURE CONTENT; SOIL WATER CONTENT; SWELLING SOILS; TEST CASES; TIME-SERIES;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; DATA SET; EXPANSIVE SOIL; FORECASTING METHOD; GROUND MOVEMENT; MOISTURE CONTENT; SHRINKAGE; SITE INVESTIGATION; SOIL MOISTURE; SWELLING; TIME SERIES;

AUSTRALASIA; AUSTRALIA; NORTH AMERICA; TEXAS; UNITED STATES;

EID: 48449105465     PISSN: 03639061     EISSN: 10969853     Source Type: Journal    
DOI: 10.1002/nag.666     Document Type: Article

References (36)

1. Wray WK, Meyer KT. Expansive clay soil. A widespread and costly geohazard. Geo-Strata, Geo Institute of ASCE, vol. 5, October 2004; 24-28.
2. Chen FH. Foundations on Expansive Soils. Elsevier Science: New York, 1988.
3. Day RW. Geotechnical Engineering Portable Handbook. McGraw-Hill: New York, 1998.
4. Fityus SG, Smith DW, Allman MA. Expansive soil test site near Newcastle. Journal of Geotechnical and Geoenvironmental Engineering 2004; 130(7):686-695.
5. Shi B, Jiang HT, Liu ZB, Fang HY. Engineering geological characteristics of expansive soils in China. Engineering Geology 2002; 67(1-2):63-71.
6. Azam S. Influence of mineralogy on swelling and consolidation of soils in eastern Saudi Arabia. Canadian Geotechnical Journal 2003; 40(5):964-975.
7. McDowell C. Interrelationships of loads, volume change, and layer thickness of soils to the behavior of engineering structures. Proceedings of the 35th Annual Meetings, Publication No. 426, Washington, DC, 1956; 754-772.
8. McKeen GR. A model for predicting expansive soil behavior. Proceedings of the 7th International Conference on Expansive Soils. Texas Tech University: Lubbock, Texas, 1992; 1-6.
9. Lytton RL. Prediction of movement in expansive clays. Proceedings of the Settlement '94 Conference on Geotechnical Special Publication No. 40, Reston, Virginia, 1994; 1827-1845.
10. PTI. Design and Construction of Post-tensioned Slabs-on-ground. Post Tensioning Institute: Phoenix, 1996.
11. Miller DJ, Durkee EB, Chao KC, Nelson JD. Simplified heave prediction for expansive soils. Proceedings of the 1st International Conference on Unsaturated Soils, Rotterdam, Netherlands, 1995; 891-897.
12. Briaud J-L, Zhang X, Moon S. Shrink test-water content method for shrink and swell predictions. Journal of Geotechnical and Geoenvironmental Engineering 2003; 129(7):590-600.
13. Coduto DP. Geotechnical Engineering Principles and Practices. Prentice-Hall: Upper Saddle River, NJ, 1999.
14. Mitchell PW. The Structural Analysis of Footings on Expansive Soil. Research Report No. 1. Kenneth W. G. Smith and Associates: Adelaide, South Australia, 1979.
15. Rizzo DM, Dougherty DE. Characterization of aquifer properties using artificial neural networks: neural kriging. Water Resources Research 1994; 30(2):483-497.
16. Besaw LE, Rizzo DM. Stochastic simulation and spatial estimation with multiple data types using artificial neural networks. Water Resources Research 2007; DOI: 10.1029/2006WR005509.
17. Schaap MG, Bouten W. Modeling water retention curves of sandy soils using neural networks. Water Resources Research 1996; 32(10):3033-3040.
18. Goh ATC. Soil laboratory data interpretation using generalized regression neural network. Civil Engineering and Environmental Systems 1999; 16:175-195.
19. Juang CH, Chen CJX, Tien YM. Appraising cone penetration test based liquefaction resistance evaluation methods: artificial neural network approach. Canadian Geotechnical Journal 1999; 36(3):443-454.
20. Habibagahi G, Bamdad A. A neural network framework for mechanical behavior of unsaturated soils. Canadian Geotechnical Journal 2003; 40:684-693.
21. Najjar YM, Basheer IA, Ali HE, McReynolds RL. Swelling potential of Kansas soils: modeling and validation using artificial neural network reliability approach. Transportation Research Record 2000; 1736:141-147.
22. Basma AA, Barakat SA, Omar M. Modeling time dependent swell of clays using sequential artificial neural networks. Environmental and Engineering Geoscience 2003; 9(3):279-288.
23. Adeli H. Neural networks in civil engineering: 1989-2000. Computer-Aided Civil and Infrastructure Engineering (Review Article) 2001; 16:126-142.
24. Rumelhart DE, Hinton E, Williams J. Learning internal representation by error propagation. Parallel Distributed Processing. MIT Press: Cambridge, MA, 1986; 318-362.
25. Specht DF. A general regression neural network. IEEE Transactions on Neural Networks 1991; 2:568-576.
26. Kohonen T. Self-organized formation of topologically correct feature maps. Biological Cybernetics 1982; 43: 56-69.
27. Hopfield JJ. Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America, vol. 79, 15 April 1982; 2554-2558.
28. Broomhead DS, Lowe D. Multivariable function interpolation and adaptive networks. Complex Systems 1988; 2:321-355.
29. Moody J, Darken C. Fast learning in networks of locally tuned processing units. Neural Computation 1989; 1:281-294.
30. Poggio T, Girosi F. Networks for approximation and learning. Proceedings of the IEEE, vol. 78, 1990; 1481-1496.
31. Hecht-Nielsen R. Counterpropagation networks. IEEE International Conference on Neural Networks, San Diego, CA, 1987; 19-32.
32. Hecht-Nielsen R. Counterpropagation networks. Applied Optics 1987; 26(23):4979-4984.
33. Hecht-Nielsen R. Applications of counterpropagation networks. Neural Networks 1988; 1:131-139.
34. Caudill M. Part I: The view from now. Using Neural Networks. AI Expert. A Miller Freeman Publication, 1995.
35. Hecht-Nielsen R. Neurocomputing. Addison-Wesley: Reading, MA, 1990.
36. Rencher AC. Methods of Multivariate Analysis. Wiley: New York, 2002.