Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …
techniques capable of delivering elegant and affordable solutions which can surpass those …
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for …
In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …
in different problems having different characteristics. Six ML approaches including Artificial …
Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions
California bearing ratio (CBR) is one of the important parameters that is used to express the
strength of the pavement subgrade of railways, roadways, and airport runways. CBR is …
strength of the pavement subgrade of railways, roadways, and airport runways. CBR is …
Modeling monthly reference evapotranspiration process in Turkey: application of machine learning methods
S Bayram, H Çıtakoğlu - Environmental Monitoring and Assessment, 2023 - Springer
In this study, the predictive power of three different machine learning (ML)-based
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …
The prediction analysis of compressive strength and electrical resistivity of environmentally friendly concrete incorporating natural zeolite using artificial neural network
AA Shahmansouri, M Yazdani, M Hosseini… - … and Building Materials, 2022 - Elsevier
To decrease the environmental and climatic effects of rising concrete consumption, more
environmentally friendly concretes are required. One approach to achieve this goal is using …
environmentally friendly concretes are required. One approach to achieve this goal is using …
[HTML][HTML] Prediction models for marshall mix parameters using bio-inspired genetic programming and deep machine learning approaches: A comparative study
This research study utilizes four machine learning techniques, ie, Multi Expression
programming (MEP), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference …
programming (MEP), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference …
[HTML][HTML] A hybrid ANN-GA model for an automated rapid vulnerability assessment of existing RC buildings
Determining the risk priorities for the building stock in highly seismic-prone regions and
making the final decisions about the buildings is one of the essential precautionary …
making the final decisions about the buildings is one of the essential precautionary …
State of art soft computing based simulation models for bearing capacity of pile foundation: a comparative study of hybrid ANNs and conventional models
Safety has been always challenging in geotechnical engineering owing to the inherently
variable nature of the soil. In pile foundations, conducting field tests is highly expensive and …
variable nature of the soil. In pile foundations, conducting field tests is highly expensive and …
[HTML][HTML] Predicting the ultimate axial capacity of uniaxially loaded cfst columns using multiphysics artificial intelligence
The object of this research is concrete-filled steel tubes (CFST). The article aimed to develop
a prediction Multiphysics model for the circular CFST column by using the Artificial Neural …
a prediction Multiphysics model for the circular CFST column by using the Artificial Neural …