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Site Characterization Model Using Artificial Neural Network and Kriging

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TLDR
In this article, the problem of site characterization is treated as a task of function approximation of the large existing data from standard penetration tests (SPTs) in three-dimensional subsurface of Bangalore, India.
Abstract
In this paper, the problem of site characterization is treated as a task of function approximation of the large existing data from standard penetration tests (SPTs) in three-dimensional subsurface of Bangalore, India. More than 2,700 field SPT values (N) has been collected from 766 boreholes spread over an area of 220 -km2 area in Bangalore, India. To get N corrected value ( Nc ) , N values have been corrected for different parameters such as overburden stress, size of borehole, type of sampler, length of connected rod. In three-dimensional analysis, the function Nc = Nc ( X,Y,Z ) , where X , Y , and Z are the coordinates of a point corresponds to Nc value, is to be approximated with which Nc value at any half-space point in Bangalore, India can be determined. An attempt has been made to develop artificial neural network (ANN) model using multilayer perceptrons that are trained with Levenberg-Marquardt back-propagation algorithm. Also, a geostatistical model based on ordinary kriging technique has been ad...

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Citations
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Journal ArticleDOI

A systematic review and meta-analysis of artificial neural network application in geotechnical engineering: theory and applications

TL;DR: The methods discussed here help the geotechnical practitioner to be familiar with the limitations and strengths of ANN compared with alternative conventional mathematical modeling methods.
Journal ArticleDOI

Probabilistic analysis of tunnel longitudinal performance based upon conditional random field simulation of soil properties

TL;DR: In this article, a new framework for the probabilistic analysis of tunnel longitudinal performance is presented, where the conditional random field theory is adopted to simulate the spatial variation of soil properties along the tunnel longitudinal direction, in which the soil properties at borehole locations can be explicitly considered.
Journal ArticleDOI

Prediction of UCS and CBR of microsilica-lime stabilized sulfate silty sand using ANN and EPR models; application to the deep soil mixing

TL;DR: In this article, the results of 90 Unconfined Compressive Strength (UCS) and California Bearing Ratio (CBR) tests on sulfate silty sand stabilized with different lime and microsilica percentages as the two main stabilizers.
Journal ArticleDOI

35 Years of (AI) in Geotechnical Engineering: State of the Art

TL;DR: The main conclusions is that the number of researches in this field increases almost exponentially, the most used (AI) technique is the Artificial Neural Networks and its enhancements where it is presents about half the researches and finally correlating soil and rock properties is the most addressed subject with about 30% of the researched.
Journal ArticleDOI

Prediction of peak ground acceleration of Iran’s tectonic regions using a hybrid soft computing technique

TL;DR: A new model is derived to predict the peak ground acceleration (PGA) utilizing a hybrid method coupling artificial neural network (ANN) and simulated annealing (SA), called SA-ANN, which is superior to the single ANN and other existing attenuation models.
References
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Journal ArticleDOI

Standard penetration test procedures and the effects in sands of overburden pressure, relative density, particle size, ageing and overconsolidation

Alec Westley Skempton
- 01 Sep 1986 - 
TL;DR: In this paper, it is shown that the blow count obtained in any given sand deposit at a particular effective overburden pressure can still vary to a significant extent depending on the method of releasing the hammer, on the type of anvil and on the length of rods.
Journal ArticleDOI

Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach

TL;DR: In this paper, a geostatistical approach is proposed for characterizing the uncertainty about the transmissivity field of an aquifer and analyzing its effect on predicted head values.
BookDOI

Geostatistics for natural resources characterization

TL;DR: In this article, Kriging is used for estimating the recoverable reserve of a mine in the presence of faults in the reserve map of a Porphyry copper mine in Canada.
Journal ArticleDOI

Introduction to neural networks for intelligent control

TL;DR: Two simple examples are presented to illustrate applications to control systems: one is fault isolation mapping, and the other involves optimization of a Hopfield network that defines a clockless analog-to-digital conversion.
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