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Neural Network Modeling of Resilient Modulus Using Routine Subgrade Soil Properties

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TLDR
In this paper, Artificial Neural Network (ANN) models are developed to correlate resilient modulus with routine properties of subgrade soils and state of stress for pavement design application, and a database is developed containing grain size distribution, Atterberg limits, standard Proctor, unconfined compression, and resilient modulation results for 97 soils from 16 different counties in Oklahoma.
Abstract
Artificial neural network (ANN) models are developed in this study to correlate resilient modulus with routine properties of subgrade soils and state of stress for pavement design application. A database is developed containing grain size distribution, Atterberg limits, standard Proctor, unconfined compression, and resilient modulus results for 97 soils from 16 different counties in Oklahoma. Of these, 63 soils (development data set) are used in training, and the remaining 34 soils (evaluation data set) from two different counties are used in the evaluation of the developed models. A commercial software, STATISTICA 7.1, is used to develop four different feedforward-type ANN models: linear network, general regression neural network, radial basis function network, and multilayer perceptrons network (MLPN). In each of these models, the input layer consists of seven nodes, one node for each of the independent variables, namely moisture content (w) , dry density ( γd ) , plasticity index (PI), percent passing ...

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International Roughness Index prediction model for flexible pavements

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Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network

TL;DR: In this paper, the elastic moduli of asphalt pavement from synthetically derived falling weight deflectometer (FWD) deflections at seven equidistant points were backcalculated.
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Prediction of the resilient modulus of flexible pavement subgrade soils using adaptive neuro-fuzzy inference systems

TL;DR: In this article, the authors investigated the potential of a powerful hybrid artificial intelligence paradigm, i.e., adaptive neuro-fuzzy inference system (ANFIS), for prediction of resilient modulus (M R ) of flexible pavements subgrade soils.
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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.
References
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Book

Building neural networks

TL;DR: This chapter discusses Neural-Network Fundamentals, which focuses on the foundations of the Fuzzy Network, and its application in Application Design and Financial Modeling.

Artificial neural network applications in geotechnical engineering

TL;DR: A review of the literature reveals that ANNs have been used successfully in pile capacity prediction, modelling soil behaviour, site characterisation, earth retaining structures, settlement of structures, slope stability, design of tunnels and underground openings, liquefaction, soil permeability and hydraulic conductivity, soil compaction and soil swelling and classification of soils.
Journal ArticleDOI

Data division for developing neural networks applied to geotechnical engineering

TL;DR: The issue of data division and its impact on ANN model performance is investigated for a case study of predicting the settlement of shallow foundations on granular soils and it is apparent that the SOM and fuzzy clustering methods are suitable approaches for data division.
Journal ArticleDOI

Resilient Properties of Subgrade Soils

TL;DR: In this paper, the authors evaluated the resilient properties of 50 typical Illinois fine-grained soils and developed regression equations for estimating resilient properties based on soil characteristics and degree of saturation, and determined average resilient properties for various soil classification groups.
Journal Article

Prediction of subgrade moduli for soil that exhibits nonlinear behavior

TL;DR: In this article, the authors developed a simple and accurate procedure to predict an equivalent one-layer subgrade modulus for a soil that exhibits nonlinear behavior in a flexible highway pavement system.
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How calculate young's modulus of soil?

The paper does not provide information on how to calculate Young's modulus of soil.