Soft computing techniques for predicting the properties of raw rice husk concrete bricks using regression-based machine learning approaches
In this study, the replacement of raw rice husk, fly ash, and hydrated lime for fine aggregate
and cement was evaluated in making raw rice husk-concrete brick. This study optimizes …
and cement was evaluated in making raw rice husk-concrete brick. This study optimizes …
Efficient compressive strength prediction of concrete incorporating recycled coarse aggregate using Newton's boosted backpropagation neural network (NB-BPNN)
This study advances the field of concrete compressive strength prediction by introducing an
innovative approach incorporating recycled coarse aggregates and the Newton's Boosted …
innovative approach incorporating recycled coarse aggregates and the Newton's Boosted …
Prognosis of flow of fly ash and blast furnace slag-based concrete: leveraging advanced machine learning algorithms
In the field of construction, the workability of concrete, specifically its ability to flow, is one of
the most concerned parameters. In recent times, the integration of artificial intelligence (AI) …
the most concerned parameters. In recent times, the integration of artificial intelligence (AI) …
Shear capacity prediction for FRCM-strengthened RC beams using Hybrid ReLU-Activated BPNN model
This study presents a robust Hybrid ReLU-Activated Backpropagation Neural Network
(BPNN) model for predicting shear strength (VFRCM) in RC beams reinforced with Fiber …
(BPNN) model for predicting shear strength (VFRCM) in RC beams reinforced with Fiber …
Enhancing load capacity prediction of column using eReLU-activated BPNN model
In structural engineering, accurately predicting the load-carrying capacity of columns is
paramount for ensuring the safety and efficiency of construction projects. This study …
paramount for ensuring the safety and efficiency of construction projects. This study …
A novel data-driven machine learning techniques to predict compressive strength of fly ash and recycled coarse aggregates based self-compacting concrete
S Aggarwal, R Singh, A Rathore, K Kapoor… - Materials Today …, 2024 - Elsevier
Compressive strength (CS) of concrete is one of the most important factors in the
construction industry and various time and effort-consuming tasks are required to measure it …
construction industry and various time and effort-consuming tasks are required to measure it …
Machine learning-based prediction of concrete strength properties with coconut shell as partial aggregate replacement: A sustainable approach in construction …
This study investigates the application of machine learning (ML) models to predict the
compressive, flexural, and split tensile strength of concrete incorporating coconut shell as a …
compressive, flexural, and split tensile strength of concrete incorporating coconut shell as a …
Comparative analysis of the influence of partial replacement of cement with supplementing cementitious materials in sustainable concrete using machine learning …
Cement manufacturing is a major contributor to climate change because of the greenhouse
gas carbon dioxide released into the atmosphere throughout the process. In this paper …
gas carbon dioxide released into the atmosphere throughout the process. In this paper …
Influence of machine learning approaches for partial replacement of cement content through waste in construction sector
For the purpose of delivering high-quality structures, efficient project management ensures
better selection of materials and methods and manpower. To successfully traverse hurdles …
better selection of materials and methods and manpower. To successfully traverse hurdles …
Predicting compressive strength of concrete with iron waste: a BPNN approach
This study presents a comprehensive exploration into predicting the compressive strength of
concrete by incorporating waste iron as a partial substitute for sand, employing a …
concrete by incorporating waste iron as a partial substitute for sand, employing a …