Machine and deep learning methods for concrete strength Prediction: A bibliometric and content analysis review of research trends and future directions
This review paper provides a detailed evaluation of the existing landscape and future trends
in applying machine learning and deep learning approaches for predicting concrete strength …
in applying machine learning and deep learning approaches for predicting concrete strength …
[HTML][HTML] A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive …
This research used gene expression programming (GEP) and multi expression
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector
Alkali-activated materials (AAMs) have recently gained attention as potentially useful
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate
Developing energy-efficient buildings considering building design parameters can help
reduce buildings' energy consumption. The energy efficiency of residential buildings is …
reduce buildings' energy consumption. The energy efficiency of residential buildings is …
An efficient machine learning approach for predicting concrete chloride resistance using a comprehensive dataset
By conducting an analysis of chloride migration in concrete, it is possible to enhance the
durability of concrete structures and mitigate the risk of corrosion. In addition, the utilization …
durability of concrete structures and mitigate the risk of corrosion. In addition, the utilization …
Forecasting the strength of micro/nano silica in cementitious matrix by machine learning approaches
This work provides an intelligent machine learning-based technique for anticipating cement
paste compressive strength incorporating nanocomposite. In this approach, artificial neural …
paste compressive strength incorporating nanocomposite. In this approach, artificial neural …
Strength estimation and feature interaction of carbon nanotubes-modified concrete using artificial intelligence-based boosting ensembles
F Zhu, X Wu, Y Lu, J Huang - Buildings, 2024 - mdpi.com
The standard approach for testing ordinary concrete compressive strength (CS) is to cast
samples and test them after different curing times. However, testing adds cost and time to …
samples and test them after different curing times. However, testing adds cost and time to …
Indirect estimation of resilient modulus (Mr) of subgrade soil: Gene expression programming vs multi expression programming
Accurate prediction of resilient modulus (MR) in compacted subgrade soil is crucial for
planning secure and environmentally friendly flexible pavement systems. This research …
planning secure and environmentally friendly flexible pavement systems. This research …
Soft computing models for prediction of bentonite plastic concrete strength
Bentonite plastic concrete (BPC) is extensively used in the construction of water-tight
structures like cut-off walls in dams, etc., because it offers high plasticity, improved …
structures like cut-off walls in dams, etc., because it offers high plasticity, improved …
[HTML][HTML] Strength predictive models of cementitious matrix by hybrid intrusion of nano and micro silica: Hyper-tuning with ensemble approaches
The incorporation of nanomaterials (NMs) in concrete will produce the utmost properties.
Nevertheless, investigational work takes a great deal of time with efforts to measure the …
Nevertheless, investigational work takes a great deal of time with efforts to measure the …