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 …

[HTML][HTML] A review on the utilization of ceramic tile waste as cement and aggregates replacement in cement based composite and a bibliometric assessment

AO Tanash, K Muthusamy, AMA Budiea… - Cleaner Engineering …, 2023 - Elsevier
The scientific community recognizes that the depletion of natural resources and solid waste
management pose inherent challenges in building material production and disposal …

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 …

A comparison of machine learning tools that model the splitting tensile strength of self-compacting recycled aggregate concrete

J de-Prado-Gil, C Palencia, P Jagadesh… - Materials, 2022 - mdpi.com
Several types of research currently use machine learning (ML) methods to estimate the
mechanical characteristics of concrete. This study aimed to compare the capacities of four …

Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

R Kazemi - Engineering Reports, 2023 - Wiley Online Library
Advanced concrete technology is the science of efficient, cost‐effective, and safe design in
civil engineering projects. Engineers and concrete designers are generally faced with the …

Machine learning algorithms to optimize the properties of bio-based poly (butylene succinate-co-butylene adipate) nanocomposites with carbon nanotubes

E Champa-Bujaico, AM Díez-Pascual… - Industrial Crops and …, 2024 - Elsevier
Abstract Poly [(butylene succinate)-co-adipate](PBSA)-based materials are gathering much
attention in the packaging industry, agriculture, and other fields owed to their …

A decade review of research trends using waste materials in the building and construction industry: a pathway towards a circular economy

R Haigh - Waste, 2023 - mdpi.com
The construction industry is among the most prominent contributors to global resource
consumption, waste production, and greenhouse gas emissions. A pivotal step toward …

Assessment of machine learning models for the prediction of rate-dependent compressive strength of rocks

Z Yang, Y Wu, Y Zhou, H Tang, S Fu - Minerals, 2022 - mdpi.com
The prediction of rate-dependent compressive strength of rocks in dynamic compression
experiments is still a notable challenge. Four machine learning models were introduced and …

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 …

Prediction and optimization of properties of concrete containing crushed stone dust and nylon fiber using response surface methodology

AF Mita, S Ray, M Haque, MH Saikat - Heliyon, 2023 - cell.com
Over-extraction of aggregates from natural sources with rapid urbanization as well as
massive waste generation in construction industry have imposed the need to utilize waste …