Support vector machine model for predicting sand liquefaction based on grid-search method

Yingyong Lixue Xuebao/Chinese Journal of Applied Mechanics

Volumn 28, Issue 1, 2011, Pages 24-28

  Zhang, Xiangdong ^a   Feng, Shengyang ^a   Wang, Changjiang ^b  

^a LIAONING TECHNICAL UNIVERSITY   (China)

^b China Railway No9 Group Co Ltd   (China)

Author keywords

Parameter of kernel function; Penalty factor; Prediction of sand liquefaction; Support vector machine, grid search method

Indexed keywords

EID: 79953100718     PISSN: 10004939     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. 1988.
2. 2000, 8(3): 379-384.
3. Seed H B, Idriss I M. Simplified procedure for evaluating soil liquefaction potential[J]. J of Geot Eng Div, ASCE, 1971, 97(SM9): 1249-1273.
4. 2001, 19(1): 35-37.
5. 2008, 29(4): 876-880.
6. 2006, 34(11): 76-79.
7. 2000, 9(1): 72-78.
8. 2005, 24(22): 4139-4144.
9. 2005, 16(2): 15-23.
10. 2004.
11. Vapnik V N. The Nature of Statistical Learning[M]. New York, Springer, 1995.
12. Vapnik V N. An overview of statistical learning theory [J]. IEEE Trans on Neural Network, 1999, 10(5): 988-999.
13. 2008.
14. 1983, 2, 26-41.
15. 2005, 14 (2): 108-114.