scholarly journals Prediction of Shear Wave Velocity on Sand Using Standard Penetration Test Results : Application of Artificial Neural Network Model

2014 ◽  
Vol 30 (5) ◽  
pp. 47-54
Author(s):  
Bum-Joo Kim ◽  
Joon-Ki Ho ◽  
Young-Cheol Hwang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shear Wave ◽  
Wave Velocity ◽  
Neural Network Model ◽  
Shear Wave Velocity ◽  
Artificial Neural Network Model ◽  
Standard Penetration Test ◽  
Test Results ◽  
Penetration Test

Shear wave velocity prediction using Elman artificial neural network

2017 ◽  
Vol 34 (4) ◽  
pp. 1281-1291 ◽  
Author(s):  
Behzad Mehrgini ◽  
Hossein Izadi ◽  
Hossein Memarian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Prediction ◽  
Artificial Neural

scholarly journals Shear wave velocity by support vector machine based on geotechnical soil properties

2014 ◽  
Vol 2 (4) ◽  
pp. 2443-2461 ◽  
Author(s):  
I. Shooshpasha ◽  
A. Kordnaeij ◽  
U. Dikmen ◽  
H. MolaAbasi ◽  
I. Amir
Keyword(s):  
Support Vector Machine ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Effective Means ◽  
Standard Penetration Test ◽  
Support Vector ◽  
Soil Parameters ◽  
Penetration Test ◽  
In Situ Tests

Abstract. Shear wave velocity (VS) is a basic engineering property implemented in evaluating the soil shear modulus. In many instances it may be preferable to determine VS indirectly by common in-situ tests, such as the Standard Penetration Test (SPT). In this paper, the relationship between VS and geotechnical soil parameters such as standard penetration test blow counts (N160), effective stress and fines content, as well as overburden stress ratio (σvo/σ′vo), is investigated. A new mode based on support vector machine (SVM) approach is proposed to correlate geotechnical parameters and VS, predicated on a total of 620 data sets, including field investigation records for the Kocaeli (Turkey, 1999) and Chi-Chi (Taiwan, 1999) earthquakes. This study addresses the question of whether Support Vector Machine (SVM) approach should be used to estimate VS based on the specified geotechnical variables, and assessing the influence of each variable on VS. Results revealed that SVM, in comparison to previous statistical relations, provides an effective means of efficiently recognizing the patterns in data and accurately predicting the VS.

Shear wave velocity measurement during a standard penetration test

1978 ◽  
Vol 6 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Yutaka Ohta ◽  
Noritoshi Goto ◽  
Hiroshi Kagami ◽  
Keishi Shiono
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Measurement ◽  
Standard Penetration Test ◽  
Penetration Test
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