Predictive models for concrete properties using machine learning and deep learning approaches: A review
MM Moein, A Saradar, K Rahmati… - Journal of Building …, 2023 - Elsevier
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …
parameter for the successful accomplishment of a tunneling project, and the proper and …
Concrete compressive strength using artificial neural networks
PG Asteris, VG Mokos - Neural Computing and Applications, 2020 - Springer
The non-destructive testing of concrete structures with methods such as ultrasonic pulse
velocity and Schmidt rebound hammer test is of utmost technical importance. Non …
velocity and Schmidt rebound hammer test is of utmost technical importance. Non …
Metamodel techniques to estimate the compressive strength of UHPFRC using various mix proportions and a high range of curing temperatures
In order to predict the compressive strength (σ c) of Ultra-high performance fiber reinforced
concrete (UHPFRC), developing a reliable and precise technique based on all main …
concrete (UHPFRC), developing a reliable and precise technique based on all main …
Prediction of pile bearing capacity using XGBoost algorithm: modeling and performance evaluation
M Amjad, I Ahmad, M Ahmad, P Wróblewski… - Applied Sciences, 2022 - mdpi.com
The major criteria that control pile foundation design is pile bearing capacity (Pu). The load
bearing capacity of piles is affected by the various characteristics of soils and the …
bearing capacity of piles is affected by the various characteristics of soils and the …
[HTML][HTML] Prediction of disc cutter life during shield tunneling with AI via the incorporation of a genetic algorithm into a GMDH-type neural network
Disc cutter consumption is a critical problem that influences work performance during shield
tunneling processes and directly affects the cutter change decision. This study proposes a …
tunneling processes and directly affects the cutter change decision. This study proposes a …
An efficient optimization approach for designing machine learning models based on genetic algorithm
Abstract Machine learning (ML) methods have shown powerful performance in different
application. Nonetheless, designing ML models remains a challenge and requires further …
application. Nonetheless, designing ML models remains a challenge and requires further …
Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition
DJ Armaghani, ET Mohamad… - … and Underground Space …, 2017 - Elsevier
The aim of this research is to develop new intelligent prediction models for estimating the
tunnel boring machine performance (TBM) by means of the rate pf penetration (PR). To …
tunnel boring machine performance (TBM) by means of the rate pf penetration (PR). To …
Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes
This study is aimed to investigate the surface eco-protection techniques for cohesive soil
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …