Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review

S Wang, P Xia, K Chen, F Gong, H Wang… - Journal of Building …, 2023 - Elsevier
Among the many sustainability challenges in the construction industry, those related to the
application of concrete and its components are the most critical. Particularly, the production …

Revealing the nature of metakaolin-based concrete materials using artificial intelligence techniques

PG Asteris, PB Lourenço, PC Roussis… - … and Building Materials, 2022 - Elsevier
In this study, a model for the estimation of the compressive strength of concretes
incorporating metakaolin is developed and parametrically evaluated, using soft computing …

[HTML][HTML] AI-Assisted optimisation of green concrete mixes incorporating recycled concrete aggregates

P Zandifaez, EA Shamsabadi, AA Nezhad… - … and Building Materials, 2023 - Elsevier
Maximising the content of supplementary cementitious materials as a partial replacement for
Portland cement and using recycled concrete aggregates as a full or partial replacement for …

Machine learning and interactive GUI for concrete compressive strength prediction

MK Elshaarawy, MM Alsaadawi, AK Hamed - Scientific Reports, 2024 - nature.com
Concrete compressive strength (CS) is a crucial performance parameter in concrete
structure design. Reliable strength prediction reduces costs and time in design and prevents …

Data-driven compressive strength prediction of fly ash concrete using ensemble learner algorithms

MS Barkhordari, DJ Armaghani, AS Mohammed… - Buildings, 2022 - mdpi.com
Concrete is one of the most popular materials for building all types of structures, and it has a
wide range of applications in the construction industry. Cement production and use have a …

A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete

T Ali, MH El Ouni, MZ Qureshi, ABMS Islam… - … and Building Materials, 2024 - Elsevier
The construction industry's growing emphasis on sustainability has driven the development
of eco-friendly concrete alternatives, such as self-compacting concrete (SCC) and …

Economic and environmental optimisation of waste cardboard kraft fibres in concrete using nondominated sorting genetic algorithm

R Haigh, Y Bouras, M Sandanayake, Z Vrcelj - Journal of Cleaner …, 2023 - Elsevier
The depletion of natural resources is accelerating due to increased construction activities
across the world. The search for alternative materials used in concrete is becoming a …

[HTML][HTML] Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric …

A Kashem, R Karim, P Das, SD Datta… - Case Studies in …, 2024 - Elsevier
The construction industry is making efforts to reduce the environmental impact of cement
production in concrete by incorporating alternative and supplementary cementitious …

Developing numerical equality to regional intensity–duration–frequency curves using evolutionary algorithms and multi-gene genetic programming

H Citakoglu, V Demir - Acta Geophysica, 2023 - Springer
This study aims to carry out regional intensity− duration− frequency (IDF) equality using the
relationship with IDF obtained from point frequency analysis. Eleven empirical equations …

Novel hybrid machine learning models including support vector machine with meta-heuristic algorithms in predicting unconfined compressive strength of organic soils …

TQ Ngo, LQ Nguyen, VQ Tran - International Journal of Pavement …, 2023 - Taylor & Francis
Each type of soil has different optimal soil stabilisation additive content. To design the
optimal soil stabilisation component, reliable and efficient models are required. The study …