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Machine learning models for predicting the axial compression capacity of cold‑formed steel elliptical hollow section columns
Tác giả: Trong-Ha Nguyen, Duc-Xuan Nguyen, Thanh-Tung Thi Nguyen, Van-Long Phan, Duy-Duan Nguyen*
238    4
Asian Journal of Civil Engineering
Quyển: 25     Trang: 1-13
Đường link/DOI: https://doi.org/10.1007/s42107-023-00886-w
Năm xuất bản: 9/2023
Cùng tác giả
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and fragility of nuclear power plant structuresBending strength diagnosis for corroded reinforced concrete beams with attendance of deterministic, random and fuzzy parametersSeismic fragility analysis of reinforced concrete piers of steel box girder bridges: A parametric studyInfluence of Squeezing Rate on Yield Stress and Viscosity of Fresh MortarA Site-Specific Response Analysis: A Case Study in Hanoi, VietnamEfficiency of flexural strengthening RC beams using fiber reinforced polymer materialsNonlinear seismic soil-structure interaction analysis of nuclear reactor building considering the effect of earthquake frequency contentReliability Assessment of Steel-Concrete Composite Beams considering Metal Corrosion EffectsA calibration of the material model for FRCPractical artificial neural network tool for predicting the axial compression capacity of circular concrete-filled steel tube columns with ultra-high-strength concreteIdentification of parameters in the crystal plasticity model for non-irradiated and irradiated A508 bainite steelEvaluation of loading capacity of corroded reinforced concrete beams using experiment and finite element methodEfficient earthquake intensity measure for seismic vulnerability of integral abutment bridgesSeismic performance evaluation of responses of NPP structure considering different numerical modelings and frequency contents of earthquakesDamage analysis of cut-and-cover tunnel structures under seismic loadingSeismic Fragilities of Bridges and Transmission Towers Considering Recorded Ground Motions in South KoreaPrediction of Critical Buckling Load of Web Tapered I‑Section Steel Columns Using Artificial Neural NetworksOptimal earthquake intensity measures for probabilistic seismic demand models of ARP1400 reactor containment buildingA machine learning-based formulation for predicting shear capacity of squat flanged RC wallsOptimal Earthquake Intensity Measures for Probabilistic Seismic Demand Models of Base-Isolated Nuclear Power 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