Utilization of self-organizing map and fuzzy clustering for site characterization using piezocone data

被引:34
作者
Das, Sarat Kumar [1 ]
Basudhar, Prabir Kumar [2 ]
机构
[1] Natl Inst Technol, Dept Civil Engn, Rourkela 769008, India
[2] Indian Inst Technol, Dept Civil Engn, Kanpur 208016, Uttar Pradesh, India
关键词
Soil stratification; Cone penetration test; Clustering; Self-organizing map; Fuzzy clustering; NEURAL-NETWORK; SPATIAL VARIABILITY; PILES; CLAY;
D O I
10.1016/j.compgeo.2008.02.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
fit this paper soft computing techniques, self-organizing maps and fuzzy clustering techniques have been proposed to isolate different layers in stratified soil based oil available cone penetration test results. The results have been compared with that obtained from cone classification chart, hierarchical and K-mean clustering techniques. It was observed that variation in result with self-organizing map (SOM) and fuzzy clustering for isolating soil layers is marginal. These techniques are found to be efficient compared to hierarchical clustering technique. The results of K-mean clustering show that the identified soil strata are similar to that obtained from cone classification chart, SOM and fuzzy clustering. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:241 / 248
页数:8
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