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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1380352
