Journal ArticleDOI
Site Characterization Model Using Artificial Neural Network and Kriging
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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...read more
Citations
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Nonparametric and data-driven interpolation of subsurface soil stratigraphy from limited data using multiple point statistics
TL;DR: An essential task in many geotechnical projects is delineation of subsurface soil stratigraphy from scatter measurements as discussed by the authors, which is a difficult and time-consuming task.
Journal ArticleDOI
Application of an Artificial Neural Network for Modeling the Mechanical Behavior of Carbonate Soils
TL;DR: In this paper, a new approach based on artificial neural networks is presented to predict the mechanical behavior of different carbonate soils, including relative density, axial strain, maximum void ratio, calcium carbonate content, and confining pressure.
Journal ArticleDOI
Three-dimensional site characterization with borehole data – A case study of Suzhou area
TL;DR: In this article, the authors presented a three-dimensional site characterization in the urban area of Suzhou where plenty of borehole explorations have been undertaken, where the relationship between the shear-wave velocity and the depth was analyzed by regression-based models.
Journal ArticleDOI
Novel Approach to Resilient Modulus Using Routine Subgrade Soil Properties
TL;DR: In this paper, Gene Expression Programming (GEP) models were developed to correlate resilient modulus with routine properties of subgrade soils and state of stress for pavement design applications, and two different correlations were developed using different combinations of the influencing parameters.
Journal ArticleDOI
Compressive Strength of Sandy Soils Stabilized with Alkali-Activated Volcanic Ash and Slag
TL;DR: In this paper, the authors considered volcanic ash as a construction material and found that environmentally friendly geopolymers have gained more attention as construction materials compared with the traditional portland cement.
References
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Journal ArticleDOI
A logical calculus of the ideas immanent in nervous activity
Warren S. McCulloch,Walter Pitts +1 more
TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Journal ArticleDOI
The perceptron: a probabilistic model for information storage and organization in the brain.
TL;DR: This article will be concerned primarily with the second and third questions, which are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory.
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The perception: a probabilistic model for information storage and organization in the brain
TL;DR: The second and third questions are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory as mentioned in this paper.
Journal ArticleDOI
Training feedforward networks with the Marquardt algorithm
TL;DR: The Marquardt algorithm for nonlinear least squares is presented and is incorporated into the backpropagation algorithm for training feedforward neural networks and is found to be much more efficient than either of the other techniques when the network contains no more than a few hundred weights.