DocumentCode
423743
Title
Evaluation of sands liquefaction potential based on SOFM neural network
Author
Sheng-Liz Hao ; Li, Min-qiang ; Kou, Ji-Song ; Liu, Yan
Author_Institution
Manage. Sch., Tianjin Univ., China
Volume
6
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
3324
Abstract
SOFM (self-organizing feature mapping) neural network is applied to evaluate sands liquefaction potential. Based on the case-historic data and the professional norms, the SOFM network model with seven input parameters and four output sorts is set up to assess sands liquefaction potential. The testing results of practical examples show that the evaluation model of sands liquefaction based on SOFM neural network is feasible and effective, therefore, it provides a new research approach to assess sands liquefaction potential.
Keywords
earthquakes; geophysics computing; liquefaction; sand; self-organising feature maps; SOFM neural network; sands liquefaction potential; self-organizing feature mapping neural network; Artificial neural networks; Earthquakes; Educational institutions; Electronic mail; Neural networks; Neurons; Predictive models; Signal resolution; Soil; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380352
Filename
1380352
Link To Document