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 …
Concrete material science: Past, present, and future innovations
H Van Damme - Cement and Concrete Research, 2018 - Elsevier
Concrete is flying off, but it is simultaneously facing tremendous challenges in terms of
environmental impact, financial needs, societal acceptance and image. Based on an …
environmental impact, financial needs, societal acceptance and image. Based on an …
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …
predicting the compressive strength (CS) of concrete, an important parameter used for …
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
DJ Armaghani, PG Asteris - Neural Computing and Applications, 2021 - Springer
Despite the extensive use of mortars materials in constructions over the last decades, there
is not yet a reliable and robust method, available in the literature, which can estimate its …
is not yet a reliable and robust method, available in the literature, which can estimate its …
A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …
engineering structures. This parameter is generally determined by conducting several tests …
Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniques
In this study, a model for the estimation of the compressive strength of concretes
incorporating metakaolin is developed and parametrically evaluated, using soft computing …
incorporating metakaolin is developed and parametrically evaluated, using soft computing …
Machine learning-based prediction for compressive and flexural strengths of steel fiber-reinforced concrete
Steel fiber-reinforced concrete (SFRC) has a performance superior to that of normal
concrete because of the addition of discontinuous fibers. The development of strengths …
concrete because of the addition of discontinuous fibers. The development of strengths …
Prediction of chloride diffusivity in concrete using artificial neural network: Modelling and performance evaluation
Chloride ingression is the main reason for causing durability degradation of reinforced
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …
A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model
J Duan, PG Asteris, H Nguyen, XN Bui… - Engineering with …, 2021 - Springer
Recycled aggregate concrete is used as an alternative material in construction engineering,
aiming to environmental protection and sustainable development. However, the …
aiming to environmental protection and sustainable development. However, the …
Predicting the compressive strength of concrete containing metakaolin with different properties using ANN
The advantages of using Metakaolin (MK) as a supplementary cementitious material have
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …