35 Years of (AI) in geotechnical engineering: state of the art
AM Ebid - Geotechnical and Geological Engineering, 2021 - Springer
It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …
geotechnical engineering, during those years many (AI) techniques were developed based …
A scientometrics review of soil properties prediction using soft computing approaches
In this world, several types of soils are available with their different engineering properties.
Determining each soil's engineering properties is difficult because the laboratory procedures …
Determining each soil's engineering properties is difficult because the laboratory procedures …
[HTML][HTML] Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
A comparison between deep learning and standalone models in predicting the compaction
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
Metaheuristic algorithms in modeling and optimization
In metaheuristic algorithms, meta-means “beyond” or “higher level.” They generally perform
better than simple heuristics. All metaheuristic algorithms use some trade-off of local search …
better than simple heuristics. All metaheuristic algorithms use some trade-off of local search …
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 …
Predict the maximum dry density of soil based on individual and hybrid methods of machine learning
This article introduces a novel technique to accurately forecast soil stabilization blends'
maximum dry density (MDD). The Naive Bayes (NB) algorithm is employed to develop …
maximum dry density (MDD). The Naive Bayes (NB) algorithm is employed to develop …
Prediction of compaction parameters of compacted soil using LSSVM, LSTM, LSBoostRF, and ANN
The present research introduces a robust approach for predicting the maximum dry density
(MDD) and optimum moisture content (OMC) of compacted soil by comparing models based …
(MDD) and optimum moisture content (OMC) of compacted soil by comparing models based …
A new multi-gene genetic programming approach to non-linear system modeling. Part II: geotechnical and earthquake engineering problems
AH Gandomi, AH Alavi - Neural Computing and Applications, 2012 - Springer
Complexity of analysis of geotechnical behavior is due to multivariable dependencies of soil
and rock responses. In order to cope with this complex behavior, traditional forms of …
and rock responses. In order to cope with this complex behavior, traditional forms of …
Prediction of compaction and strength properties of amended soil using machine learning
WZ Taffese, KA Abegaz - Buildings, 2022 - mdpi.com
In the current work, a systematic approach is exercised to monitor amended soil reliability for
a housing development program to holistically understand the targeted material mixture and …
a housing development program to holistically understand the targeted material mixture and …