Cited by A novel method for tracing gasoline using GC-IRMS and Relief-Stacking fusion model

An Ultrasonic-AI Hybrid Approach for Predicting Void Defects in Concrete-Filled Steel Tubes via Enhanced XGBoost with Bayesian Optimization DOI

Shuai Wan, Shaozhi Li, George Z. Chen

et al.

Case Studies in Construction Materials, Journal Year: 2025, Volume and Issue: unknown, P. e04359 - e04359

Published: Feb. 1, 2025

Language: Английский

Citations

A predictive model for the freeze-thaw concrete durability index utilizing the deeplabv3+ model with machine learning DOI

Daming Luo,

Xudong Qiao,

Ditao Niu

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 459, P. 139788 - 139788

Published: Jan. 1, 2025

Language: Английский

Citations

A review on properties and multi-objective performance predictions of concrete based on machine learning models DOI

Bowen Ni,

Md Zillur Rahman, Shuaicheng Guo

et al.

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112017 - 112017

Published: Feb. 1, 2025

Language: Английский

Citations

Explainable hybridized ensemble machine learning for the prognosis of the compressive strength of recycled plastic-based sustainable concrete with experimental validation DOI

Sanjog Chhetri Sapkota, Ajay Yadav,

Ajaya Khatri

et al.

Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 7(6), P. 6073 - 6096

Published: Aug. 21, 2024

Language: Английский

Citations

A novel technique for multi-objective sustainable decisions for pavement maintenance and rehabilitation DOI

Hamed Naseri,

Amirreza Aliakbari,

Mahdie Asl Javadian

et al.

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 20, P. e03037 - e03037

Published: March 6, 2024

To maintain pavement in good condition while considering financial costs and sustainability, it is necessary to develop a comprehensive management plan. Pavement Maintenance Rehabilitation (M&R) consists of two essential components: firstly, predicting the within specified timeframe, secondly, employing an appropriate optimization algorithm. This study utilized three ensemble learning techniques including extreme gradient boosting, categorical light boosting machine accurate predictions about condition. Subsequently, most prediction technique, which was combined with non-dominated sorting genetic algorithm III multi-objective metaheuristic algorithm, resulting hybrid technique that offers highly maintenance rehabilitation planning. Although previous studies neglected important criteria such as road closure process, this takes into account four objective functions greenhouse gas emission, M&R cost, condition, be minimized over 5-year program. process generated 52 optimal solutions known Pareto front. compare rank various plans, grey relational analysis employed. The results suggested there direct correlation between GHG emissions. Minimizing only conditions planning can significantly increase emissions, costs, closure. Implementing preventive actions reduce overall medium are recommended optimize pavements.

Language: Английский

Citations

Innovative Approaches, Challenges, and Future Directions for Utilizing Carbon Dioxide in Sustainable Concrete Production DOI

Dong Lu, Fulin Qu, Chao Zhang

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 110904 - 110904

Published: Sept. 1, 2024

Language: Английский

Citations

Prediction of split tensile strength of recycled aggregate concrete leveraging explainable hybrid XGB with optimization algorithm DOI

Sanjog Chhetri Sapkota,

Sagar Sapkota,

Gaurav Saini

et al.

Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 7(4), P. 4343 - 4359

Published: May 31, 2024

Language: Английский

Citations

Finite-Element-Based Time-Dependent Service Life Prediction for Carbonated Reinforced Concrete Aqueducts DOI

Lan Zhang,

R F He,

Long‐Wen Zhang

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(1), P. 463 - 463

Published: Jan. 6, 2025

This study proposes a time-dependent reliability analysis method for aqueduct structures based on concrete carbonation and finite element analysis. The primary goal of this is to improve the assessment reinforced aqueducts by incorporating environmental factors such as over time. First, three-dimensional model established using Midas 2022 Civil software, time-varying function derived from predictive depth. Point estimation then integrated with structural calculate first four moments random variables functions carbonation. Additionally, original performance transformed into normal distribution dual power transformation Jarque–Bera test. high-order unscented (HUT) subsequently employed estimate function, facilitating calculation indices carbonated aqueduct. Based index data, corresponding different time points fitted applied service life prediction. results demonstrate that proposed effectively reduces large errors associated fourth-moment in calculating indices. Furthermore, comparison Monte Carlo simulation (MCS) validates high efficiency accuracy method, offering valuable tool addressing challenges exposed other

Language: Английский

Citations

Study of Entropy Weight-Grey theory-BP Network life prediction Model of unit silica fume concrete lining under the influence of carbonation-sulfate freeze-thaw cycle erosion DOI

Zhi‐Min Chen, Meisheng Yi, Jiqiang Zhang

et al.

Research in Cold and Arid Regions, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

Research on carbonation percentage of carbonated recycled concrete fine aggregate: experimental investigation and machine learning prediction DOI

Mingyang Ma, Meng Chen, Tong Zhang

et al.

Journal of Sustainable Cement-Based Materials, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 22

Published: Jan. 19, 2025

Language: Английский

Citations