Prediction of compressive strength of geopolymer concrete landscape design: Application of the novel hybrid RF–GWO–XGBoost algorithm

J Zhang, R Wang, Y Lu, J Huang - Buildings, 2024‏ - mdpi.com
Landscape geopolymer concrete (GePoCo) with environmentally friendly production
methods not only has a stable structure but can also effectively reduce environmental …

Towards designing durable sculptural elements: Ensemble learning in predicting compressive strength of fiber-reinforced nano-silica modified concrete

R Wang, J Zhang, Y Lu, J Huang - Buildings, 2024‏ - mdpi.com
Fiber-reinforced nano-silica concrete (FrRNSC) was applied to a concrete sculpture to
address the issue of brittle fracture, and the primary objective of this study was to explore the …

[HTML][HTML] Predicting the compressive strength of the cement-fly ash–slag ternary concrete using the firefly algorithm (fa) and random forest (rf) hybrid machine-learning …

J Huang, MMS Sabri, DV Ulrikh, M Ahmad… - Materials, 2022‏ - mdpi.com
Concrete is the most widely used material in construction. It has the characteristics of strong
plasticity, good economy, high safety, and good durability. As a kind of structural material …

Exploring the viability of AI-aided genetic algorithms in estimating the crack repair rate of self-healing concrete

Q Tian, Y Lu, J Zhou, S Song, L Yang… - Reviews on Advanced …, 2024‏ - degruyter.com
As a potential replacement for traditional concrete, which has cracking and poor durability
issues, self-healing concrete (SHC) has been the research subject. However, conducting lab …

Towards a reliable design of geopolymer concrete for green landscapes: a comparative study of tree-based and regression-based models

R Wang, J Zhang, Y Lu, S Ren, J Huang - Buildings, 2024‏ - mdpi.com
The design of geopolymer concrete must meet more stringent requirements for the
landscape, so understanding and designing geopolymer concrete with a higher …

Development of a new stacking model to evaluate the strength parameters of concrete samples in laboratory

J Huang, M Zhou, J Zhang, J Ren, NI Vatin… - Iranian journal of …, 2022‏ - Springer
In this research, a new idea was implemented to combine different models of artificial
intelligence (AI) for evaluating the strength parameters of concrete samples in laboratory. To …

Compressive strength of waste-derived cementitious composites using machine learning

Q Tian, Y Lu, J Zhou, S Song, L Yang… - Reviews on Advanced …, 2024‏ - degruyter.com
Marble cement (MC) is a new binding material for concrete, and the strength assessment of
the resulting materials is the subject of this investigation. MC was tested in combination with …

[HTML][HTML] Intelligent design of building materials: Development of an ai-based method for cement-slag concrete design

F Zhu, X Wu, M Zhou, MMS Sabri, J Huang - Materials, 2022‏ - mdpi.com
Cement-slag concrete has become one of the most widely used building materials
considering its economical advantage and satisfying uniaxial compressive strength (UCS) …

[HTML][HTML] Intelligent design of construction materials: a comparative study of AI approaches for predicting the strength of concrete with blast furnace slag

X Wu, F Zhu, M Zhou, MMS Sabri, J Huang - Materials, 2022‏ - mdpi.com
Concrete production by replacing cement with green materials has been conducted in
recent years considering the strategy of sustainable development. This study researched the …

Splitting tensile strength prediction of Metakaolin concrete using machine learning techniques

Q Li, G Ren, H Wang, Q Xu, J Zhao, H Wang, Y Ding - Scientific Reports, 2023‏ - nature.com
Splitting tensile strength (STS) is an important mechanical property of concrete. Modeling
and predicting the STS of concrete containing Metakaolin is an important method for …