Predicting residual strength of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) exposed to elevated temperatures using machine learning

Case Studies in Construction Materials, Год журнала: 2024, Номер 22, С. e04112 - e04112

Опубликована: Дек. 11, 2024

Язык: Английский

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Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine

Water, Год журнала: 2023, Номер 15(13), С. 2453 - 2453

Опубликована: Июль 4, 2023

The likelihood of surface water and groundwater contamination is higher in regions close to landfills due the possibility leachate percolation, which a potential source pollution. Therefore, proposing reliable framework for monitoring parameters an essential task managers authorities quality control. For this purpose, efficient hybrid artificial intelligence model based on grey wolf metaheuristic optimization algorithm extreme learning machine (ELM-GWO) used predicting landfill (COD BOD5) (turbidity EC) at Saravan landfill, Rasht, Iran. In study, samples were collected from wells. Moreover, concentration different physico-chemical heavy metal (Cd, Cr, Cu, Fe, Ni, Pb, Mn, Zn, turbidity, Ca, Na, NO3, Cl, K, COD, EC, TDS, pH, K). results obtained ELM-GWO compared with four models: multivariate adaptive regression splines (MARS), (ELM), multilayer perceptron neural network (MLPANN), integrated (MLPANN-GWO). study confirm that considerably enhanced predictive performance MLPANN-GWO, ELM, MLPANN, MARS models terms root-mean-square error, respectively, by 43.07%, 73.88%, 74.5%, 88.55% COD; 23.91%, 59.31%, 62.85%, 77.71% BOD5; 14.08%, 47.86%, 53.43%, 57.04% turbidity; 38.57%, 59.64%, 67.94%, 74.76% EC. can be applied as robust approach investigating sites.

Язык: Английский

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Prediction of compressive strength of high-performance concrete using optimization machine learning approaches with SHAP analysis

Journal of Building Pathology and Rehabilitation, Год журнала: 2024, Номер 9(2)

Опубликована: Май 24, 2024

Язык: Английский

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Machine Learning for Defect Condition Rating of Wall Wooden Columns in Ancient Buildings

Case Studies in Construction Materials, Год журнала: 2025, Номер unknown, С. e04458 - e04458

Опубликована: Фев. 1, 2025

Язык: Английский

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How machine learning can transform the future of concrete

Asian Journal of Civil Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 14, 2025

Язык: Английский

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Ultrasonic detection and deep learning for high-precision concrete strength prediction

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112372 - 112372

Опубликована: Март 1, 2025

Язык: Английский

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Optimized neural network for soil moisture prediction in precision agriculture

Measurement, Год журнала: 2025, Номер unknown, С. 117380 - 117380

Опубликована: Март 1, 2025

Язык: Английский

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Prediction of compressive strength of blended concrete with Alccofine and GGBFS by applying ensemble machine learning algorithms

Journal of Structural Integrity and Maintenance, Год журнала: 2025, Номер 10(2)

Опубликована: Апрель 3, 2025

Язык: Английский

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Compressive Strength Prediction of Geopolymers Using Stacking Ensemble and Fuzzy Splitting

Iranian Journal of Science and Technology Transactions of Civil Engineering, Год журнала: 2025, Номер unknown

Опубликована: Апрель 23, 2025

Язык: Английский

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Anticipation of shear strength of recycled aggregate reinforced concrete beams: a novel hybrid RF-TGC model and realistic implementation

Asian Journal of Civil Engineering, Год журнала: 2024, Номер unknown

Опубликована: Сен. 16, 2024

Язык: Английский

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