Data analysis in pavement engineering: An overview
Extensive studies on data analysis have been conducted to address pavement engineering
problems including material and structure design, performance evaluation, maintenance …
problems including material and structure design, performance evaluation, maintenance …
Data-driven estimation models of asphalt mixtures dynamic modulus using ANN, GP and combinatorial GMDH approaches
The objective of the present study is to develop and evaluate machine learning-based
prediction models, employing the artificial neural networks (ANNs), Genetic Programming …
prediction models, employing the artificial neural networks (ANNs), Genetic Programming …
Investigating the effects of ensemble and weight optimization approaches on neural networks' performance to estimate the dynamic modulus of asphalt concrete
This study hybridized the ensemble and weight optimization approaches with an artificial
neural network (ANN) algorithm to forecast the dynamic modulus (E*) of asphalt concrete …
neural network (ANN) algorithm to forecast the dynamic modulus (E*) of asphalt concrete …
Optimizing asphalt mix design through predicting the rut depth of asphalt pavement using machine learning
Generally, when asphalt concrete (AC) is in the design phase, the rutting development of the
actual pavement is always not considered. Traditional simulative wheel-tracking tests, which …
actual pavement is always not considered. Traditional simulative wheel-tracking tests, which …
Application of non-linear regression analysis and artificial intelligence algorithms for performance prediction of hard rock TBMs
A Salimi, J Rostami, C Moormann, A Delisio - Tunnelling and Underground …, 2016 - Elsevier
Prediction of machine performance is an essential step for planning, cost estimation and
selection of excavation method to assure success of tunneling operation by hard rock TBMs …
selection of excavation method to assure success of tunneling operation by hard rock TBMs …
Prediction of blast-induced rock movement during bench blasting: use of gray wolf optimizer and support vector regression
A large ore loss and dilution can be expected when using a pre-blast ore boundary for
shovel guidance because of the movement and re-distribution of ore in the muck pile under …
shovel guidance because of the movement and re-distribution of ore in the muck pile under …
Involving prediction of dynamic modulus in asphalt mix design with machine learning and mechanical-empirical analysis
Dynamic modulus (E∗) plays a dominant role in comprehensively capturing the mechanical
behavior of asphalt mixture. Many researchers tried to consider E∗ as a performance …
behavior of asphalt mixture. Many researchers tried to consider E∗ as a performance …
Pre-trained deep learning for hot-mix asphalt dynamic modulus prediction with laboratory effort reduction
Evaluating the hot mix asphalt (HMA) expected performance is one of the significant aspects
of highways research. Dynamic modulus (E*) presents itself as a fundamental mechanistic …
of highways research. Dynamic modulus (E*) presents itself as a fundamental mechanistic …
Improving asphalt mix design considering international roughness index of asphalt pavement predicted using autoencoders and machine learning
Scientific asphalt mix design can improve the engineering properties of asphalt mixture, thus
further slowing the growth of international roughness index (IRI). To avoid the occurrence of …
further slowing the growth of international roughness index (IRI). To avoid the occurrence of …
Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction
Aiming at the problems of the traditional method of assessing distribution of particle size in
bench blasting, a support vector machines (SVMs) regression methodology was used to …
bench blasting, a support vector machines (SVMs) regression methodology was used to …