Research on Optimization of Network Attack Detection Model Based on Imbalanced Data DOI

思瑶 杨

Computer Science and Application, Год журнала: 2024, Номер 14(11), С. 1 - 10

Опубликована: Янв. 1, 2024

Язык: Английский

Compressive strength prediction models for concrete containing nano materials and exposed to elevated temperatures DOI Creative Commons
Hany A. Dahish, Ahmed D. Almutairi

Results in Engineering, Год журнала: 2025, Номер unknown, С. 103975 - 103975

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

3
Dynamic mechanical properties of concrete containing cellulose fiber subject to coupling action of multiple impacts and high temperature erosion: Effects and mechanism DOI

Hansong Wu,

Aiqin Shen, Jinxi Zhang

и другие.

Construction and Building Materials, Год журнала: 2025, Номер 471, С. 140714 - 140714

Опубликована: Март 11, 2025

Язык: Английский

Процитировано

0
The Application of Response Surface Methodology and Machine Learning for Predicting the Compressive Strength of Recycled Aggregate Concrete Containing Polypropylene Fibers and Supplementary Cementitious Materials DOI Open Access
Mohammed K. Alkharisi, Hany A. Dahish

Sustainability, Год журнала: 2025, Номер 17(7), С. 2913 - 2913

Опубликована: Март 25, 2025

The construction industry’s development trend has resulted in a large volume of demolished concrete. Improving the efficiency proper use this waste as recycled aggregate (RA) concrete is promising solution. In study, we utilized response surface methodology (RSM) and three machine learning (ML) techniques—the M5P algorithm, random forest (RF) extreme gradient boosting (XGB)—to optimize predict compressive strength (CS) RA containing fly ash (FA), silica fume (SF), polypropylene fiber (PPF). To build models, results regarding 529 data points were used dataset with varying numbers input parameters (out total ten). CS quadratic model under RSM exhibited acceptable prediction accuracy. best was found 100% consisting coarse aggregate, 1.13% PPF by concrete, 7.90% FA, 5.30% SF partial replacements binders weight. XGB superior performance high accuracy, higher R² lower values errors, depicted MAE, RMSE, MAPE, when compared to other developed models. Furthermore, SHAP analysis showed that had positive impact on predicting CS, but curing age superplasticizer dose highest

Язык: Английский

Процитировано

0
Fire performance of concrete: A comparative study between cement concrete and geopolymer concrete & its application - A state of art-review DOI Creative Commons
Éva Lublóy, Balamurali Kanagaraj,

N. Anand

и другие.

Case Studies in Chemical and Environmental Engineering, Год журнала: 2025, Номер unknown, С. 101212 - 101212

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Prediction of multi-stage recrystallization behavior of AerMet100 high-strength steel based on deep learning DOI Creative Commons

Z.J. Wang,

Hongwu Chen, Jingyu Zhang

и другие.

Journal of Materials Research and Technology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Prediction of the tensile properties of A356 casted alloy based on the pore structure using machine learning DOI Creative Commons

Ágota Kazup,

Attila Garami,

Zoltán Gácsi

и другие.

Materials Science and Engineering A, Год журнала: 2025, Номер unknown, С. 148338 - 148338

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Research on Optimization of Network Attack Detection Model Based on Imbalanced Data DOI

思瑶 杨

Computer Science and Application, Год журнала: 2024, Номер 14(11), С. 1 - 10

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0