[HTML][HTML] Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive …

P Das, A Kashem - Case Studies in Construction Materials, 2024 - Elsevier
Ultra-high-performance concrete (UHPC) is a sustainable construction material; it can be
applied as a substitute for cement concrete. Artificial intelligence methods have been used …

Compressive strength prediction of high-strength concrete using long short-term memory and machine learning algorithms

H Chen, X Li, Y Wu, L Zuo, M Lu, Y Zhou - Buildings, 2022 - mdpi.com
Compressive strength is an important mechanical property of high-strength concrete (HSC),
but testing methods are usually uneconomical, time-consuming, and labor-intensive. To this …

Compressive strength prediction of high-strength concrete using hybrid machine learning approaches by incorporating SHAP analysis

A Kashem, P Das - Asian Journal of Civil Engineering, 2023 - Springer
Concrete is the most extensively used construction material, and cement is its main
component. Hybrid machine learning models attract researchers in building materials due to …

Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment

SD Latif - Environmental Science and Pollution Research, 2021 - Springer
One of the most critical parameters in concrete design is compressive strength. As the
compressive strength of concrete is correctly measured, time and cost can be decreased …

Generalized uncertainty in surrogate models for concrete strength prediction

MA Hariri-Ardebili, G Mahdavi - Engineering Applications of Artificial …, 2023 - Elsevier
Applied soft computing has been widely used to predict material properties, optimal mixture,
and failure modes. This is challenging, especially for the highly nonlinear behavior of brittle …

Prediction of the compressive strength of Flyash and GGBS incorporated geopolymer concrete using artificial neural network

U Sharma, N Gupta, M Verma - Asian Journal of Civil Engineering, 2023 - Springer
Many numerical computation methods have been devised and put to use in a variety of
science and technology disciplines in the twenty-first century. Artificial neural networks …

[HTML][HTML] ANN based predictive mimicker for mechanical and rheological properties of eco-friendly geopolymer concrete

F Rehman, SA Khokhar, RA Khushnood - Case Studies in Construction …, 2022 - Elsevier
Due to an increase in global warming, the construction industry, like the rest of the world is
turning towards sustainable solutions. The construction industry is the major contributor to …

Prediction of compressive strength of fly ash-based geopolymer concrete using supervised machine learning methods

AQ Khan, MH Naveed, MD Rasheed, P Miao - Arabian Journal for …, 2024 - Springer
The use of fly ash (FA)-based geopolymer concrete as a low-carbon and eco-friendly
substitute to Portland cement concrete has gained attention in recent years. However …

[HTML][HTML] Modeling the effect of implementation of artificial intelligence powered image analysis and pattern recognition algorithms in concrete industry

A Waqar, N Bheel, BA Tayeh - Developments in the Built Environment, 2024 - Elsevier
AI-powered image analysis and pattern recognition algorithms (IAPRA) are renowned for
their capacity to identify concrete flaws, assess strength characteristics, and anticipate the …

Unveiling the Potential of AI Assistants: A Review of AI in Building Materials Selection

AP Wibowo - Journal of Artificial Intelligence in Architecture, 2024 - ojs.uajy.ac.id
Abstract Fast-advancing Artificial Intelligence (AI) has transformed many industries,
including construction. AI offers innovative solutions to increase efficiency and effectiveness …