Artificial intelligence algorithms for prediction and sensitivity analysis of mechanical properties of recycled aggregate concrete: A review
Using recycled aggregates generated from demolition waste for concrete production is a
promissory option to reduce the environmental footprint of the built environment. However …
promissory option to reduce the environmental footprint of the built environment. However …
Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
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 …
Artificial intelligence to model the performance of concrete mixtures and elements: a review
A Behnood, EM Golafshani - Archives of Computational Methods in …, 2022 - Springer
Concrete is the most widely used man-made material in the construction of structures,
pavements, bridges, dams, and infrastructures. Depending on the type of components and …
pavements, bridges, dams, and infrastructures. Depending on the type of components and …
Estimating compressive strength of concrete using neural electromagnetic field optimization
Concrete compressive strength (CCS) is among the most important mechanical
characteristics of this widely used material. This study develops a novel integrative method …
characteristics of this widely used material. This study develops a novel integrative method …
Development of deep neural network model to predict the compressive strength of rubber concrete
This paper presents an innovative development process of a Deep Neural Network model to
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
predict the compressive strength of rubber concrete. To this goal, a rubber concrete …
Predictive modeling of mechanical properties of silica fume-based green concrete using artificial intelligence approaches: MLPNN, ANFIS, and GEP
Silica fume (SF) is a mineral additive that is widely used in the construction industry when
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
Iterative application of generative adversarial networks for improved buried pipe detection from images obtained by ground‐penetrating radar
PJ Chun, M Suzuki, Y Kato - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Ground‐penetrating radar (GPR) is widely used to determine the location of buried pipes
without excavation, and machine learning has been researched to automatically identify the …
without excavation, and machine learning has been researched to automatically identify the …
A hierarchical framework for improving ride comfort of autonomous vehicles via deep reinforcement learning with external knowledge
Ride comfort plays an important role in determining the public acceptance of autonomous
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Artificial intelligence algorithms have recently demonstrated their efficacy in accurately
predicting concrete properties by optimizing mixing proportions and overcoming design …
predicting concrete properties by optimizing mixing proportions and overcoming design …