Evaluation of sands liquefaction potential based on SOFM neural network
Sheng-Liz Hao; Min-Qiang Li; Ji-Song Kou; Yan Liu
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Volume 6, Issue , 26-29 Aug. 2004 Page(s): 3324 - 3327 vol.6
Digital Object Identifier  
Summary: 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.

» View citation and abstract

Log in by entering your IEEE Web Account Username and Password.

IEEE Communications Society members: If you subscribe to the IEEE Electronic Periodicals Package or IEEE Electronic Periodicals Package Plus, you must access your subscription at www.comsoc.org.

Check with your librarian, information professional, or system manager to determine if you need to log in. Please complete the online Technical Support Form if you need assistance.

Select the Purchase History link to access the document. You will have 5 Days after purchase to access the Full Text PDF. Please complete the online Technical Support Form if you need assistance.

• Search and access Abstract records free of charge
• Register for table of contents alerts
• Purchase Full Text PDF documents

» Learn more about subscription options or how to become an IEEE Member.