Predicting the Young's modulus of frozen sand using machine learning approaches: State-of-the-art review
RS Benemaran, M Esmaeili-Falak - Geomechanics and …, 2023 - koreascience.kr
Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF)
is a most important scientific topic in soil improvement and geotechnical engineering. In …
is a most important scientific topic in soil improvement and geotechnical engineering. In …
State-of-the-art review on permanent deformation characterization of asphalt concrete pavements
Rutting is one of the significant distresses in flexible pavements. Examining the methods to
decrease permanent deformation is of considerable importance to provide long service life …
decrease permanent deformation is of considerable importance to provide long service life …
Improved arithmetic optimization algorithm and its application to carbon fiber reinforced polymer-steel bond strength estimation
X Shi, X Yu, M Esmaeili-Falak - Composite Structures, 2023 - Elsevier
In order to restore steel structures, bonding carbon fiber reinforced polymer (CFRP)
laminates have been widely used. The bond strength (PU) between the CFRP and steel …
laminates have been widely used. The bond strength (PU) between the CFRP and steel …
Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms
In this study, gene expression programming (GEP) and multi gene expression programming
(MEP) are utilized to formulate new prediction models for determining the compaction …
(MEP) are utilized to formulate new prediction models for determining the compaction …
A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning
Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock
salt are multi-porosity porous media in which pores of different scales may co-exist in the …
salt are multi-porosity porous media in which pores of different scales may co-exist in the …
A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series
Developing a hydrological forecasting model based on past records is crucial to effective
hydropower reservoir management and scheduling. Traditionally, time series analysis and …
hydropower reservoir management and scheduling. Traditionally, time series analysis and …
A robust data mining approach for formulation of geotechnical engineering systems
A Hossein Alavi, A Hossein Gandomi - Engineering Computations, 2011 - emerald.com
Purpose–The complexity of analysis of geotechnical behavior is due to multivariable
dependencies of soil and rock responses. In order to cope with this complex behavior …
dependencies of soil and rock responses. In order to cope with this complex behavior …
Multi-stage genetic programming: a new strategy to nonlinear system modeling
AH Gandomi, AH Alavi - Information Sciences, 2011 - Elsevier
This paper presents a new multi-stage genetic programming (MSGP) strategy for modeling
nonlinear systems. The proposed strategy is based on incorporating the individual effect of …
nonlinear systems. The proposed strategy is based on incorporating the individual effect of …
Estimation of soil cation exchange capacity using genetic expression programming (GEP) and multivariate adaptive regression splines (MARS)
The soil cation exchange capacity (CEC) is one of the main soil chemical properties, which
is required in various fields such as environmental and agricultural engineering as well as …
is required in various fields such as environmental and agricultural engineering as well as …
[PDF][PDF] State of the art of artificial neural networks in geotechnical engineering
Over the last few years, artificial neural networks (ANNs) have been used successfully for
modeling almost all aspects of geotechnical engineering problems. Whilst ANNs provide a …
modeling almost all aspects of geotechnical engineering problems. Whilst ANNs provide a …