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Compressive strength prediction of ternary blended geopolymer concrete using artificial neural networks and support vector regression
The development of ternary blended geopolymers is one of the recent advancements in
geopolymer concrete technology, which utilizes different source materials in various …
geopolymer concrete technology, which utilizes different source materials in various …
Evaluating machine learning algorithms for predicting compressive strength of concrete with mineral admixture using long short-term memory (LSTM) Technique
The prediction of compressive strength in concrete holds essential significance within the
construction industry, maintaining the structural reliability of important infrastructure like …
construction industry, maintaining the structural reliability of important infrastructure like …
Soft computing-based investigation of mechanical properties of concrete using ready-mix concrete waste water as partial replacement of mixing portable water
The construction industry is known to have a substantial impact on the Earth's freshwater
resources. However, in the twenty-first century, the depletion of water resources and the …
resources. However, in the twenty-first century, the depletion of water resources and the …
Enhancing high-strength self-compacting concrete properties through Nano-silica: Analysis and prediction of mechanical strengths
This study investigates the mechanical properties of high-strength self-compacting concrete
(HSSCC) through rigorous laboratory testing. Six input parameters—cement, water-cement …
(HSSCC) through rigorous laboratory testing. Six input parameters—cement, water-cement …
The influence of fly ash and blast furnace slag on the compressive strength of high-performance concrete (HPC) for sustainable structures
The development of high-performance concrete (HPC) has shown a revolution in the built
environment in terms sustainability and performance. In this research paper, the …
environment in terms sustainability and performance. In this research paper, the …
Surrogate model-based prediction of settlement in foundation over cavity for reliability analysis
The stability of the foundations of a building may be seriously harmed by excavations (eg,
tunneling) or cavities (eg, rock dissolution) underneath. It may be difficult and time …
tunneling) or cavities (eg, rock dissolution) underneath. It may be difficult and time …
Prediction of compressive strength of glass fiber-reinforced self-compacting concrete interpretable by machine learning algorithms
Self-compacting concrete (SCC) is a versatile construction material known for its ability to
consolidate naturally under its own weight, making it well suited for challenging placements …
consolidate naturally under its own weight, making it well suited for challenging placements …
An integrated evaluation of waste materials containing recycled asphalt fine aggregates using central composite design
This research examines the feasibility of using washed recycled fine aggregates (WRFA) as
a substitute for natural virgin aggregates in concrete. The aim is to develop novel models …
a substitute for natural virgin aggregates in concrete. The aim is to develop novel models …
One‐Dimensional‐Convolutional Neural Network (1D‐CNN) Based Reliability Analysis of Foundation Over Cavity Incorporating the Effect of Simulated Noise
This paper presents a thorough reliability assessment of cavity foundation systems involving
the generation of 272 datasets using Plaxis 2D automation. The parameters were …
the generation of 272 datasets using Plaxis 2D automation. The parameters were …
Optimizing shallow foundation design: a machine learning approach for bearing capacity estimation over cavities
The presence of excavations or cavities beneath the foundations of a building can have a
significant impact on their stability and cause extensive damage. Traditional methods for …
significant impact on their stability and cause extensive damage. Traditional methods for …