Standout Papers

Efficient estimating compressive strength of ultra-high performance concrete using XGBoost model 2022 2026 2023 2024116
  1. Efficient estimating compressive strength of ultra-high performance concrete using XGBoost model (2022)
    Joaquín Abellán García, Seunghye Lee et al. Journal of Building Engineering

Immediate Impact

12 from Science/Nature 64 standout
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Citing Papers

Uncertainty-oriented physics-informed long short-term memory (UOPI-LSTM) network framework for dynamic force identification with interval uncertainties
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Combined influence of modified recycled concrete aggregate and metakaolin on high-strength concrete production: Experimental assessment and machine learning quantifications with advanced SHAP and PDP analyses
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Works of Seunghye Lee being referenced

Efficient estimating compressive strength of ultra-high performance concrete using XGBoost model
2022 Standout
Prediction compressive strength of cement-based mortar containing metakaolin using explainable Categorical Gradient Boosting model
2022
and 1 more

Author Peers

Author Last Decade Papers Cites
Seunghye Lee 1141 544 458 86 2.1k
Yahui Zhang 763 875 578 129 2.0k
Ning Zhang 1037 369 238 80 2.2k
Tuan Ngoc Nguyen 1270 893 321 52 2.8k
Zubaidah Ismail 989 402 333 105 2.1k
Majid Khorami 982 314 285 57 2.0k
Shuai Li 498 213 559 123 1.6k
Nan Ye 984 204 670 148 2.8k
A. Andrade‐Campos 464 681 820 112 1.5k
Ali Shariati 1486 551 263 45 2.5k
Tien-Thinh Le 1976 341 401 68 2.8k

All Works

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2026