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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50505

Title: CPT-BASED LIQUEFACTION ASSESSMENT BY USING FUZZY-NEURAL NETWORK
Authors: Shuh-Gi Chern
Ching-Yinn Lee
Chin-Chen Wang
Contributors: 國立臺灣海洋大學:河海工程學系
Keywords: fuzzy-neural
network
CPT
liquefaction
Date: 2008
Issue Date: 2018-10-12T07:02:25Z
Publisher: Journal of marine science and technology
Abstract: Abstract: Because of the increasing popularity worldwide of the cone
penetration test (CPT) for site characterization, significant
progress on the simplified CPT-based methods has been made
for evaluation of earthquake induced liquefaction potential of
soils. In this study, a fuzzy-neural network combined with 466
CPT field observations is developed to evaluate liquefaction
potential of soils. The proposed model combines fuzzy theory
with subtractive clustering algorithm to establish a fuzzy-neural
system. The study indicates that fuzzy-neural network can
successfully describe the complex relationship between seismic
parameters, soil parameters, and the liquefaction potential. The
fuzzy-neural network model is found to have very good predictive
ability and is expected to be very reliable for evaluation
of liquefaction potential.
Relation: 16(2) pp.139-148
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50505
Appears in Collections:[河海工程學系] 期刊論文

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