Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to ...Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core.To address this limitation,this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer(PKO),a nature-inspired algorithm,to enhance the accuracy of shear strength prediction for CFST columns.Additionally,quantile regression is employed to construct prediction intervals for the ultimate shear force,while the Asymmetric Squared Error Loss(ASEL)function is incorporated to mitigate overestimation errors.The computational results demonstrate that the PKO-XGBoost model delivers superior predictive accuracy,achieving a Mean Absolute Percentage Error(MAPE)of 4.431%and R2 of 0.9925 on the test set.Furthermore,the ASEL-PKO-XGBoost model substantially reduces overestimation errors to 28.26%,with negligible impact on predictive performance.Additionally,based on the Genetic Algorithm(GA)and existing equation models,a strength equation model is developed,achieving markedly higher accuracy than existing models(R^(2)=0.934).Lastly,web-based Graphical User Interfaces(GUIs)were developed to enable real-time prediction.展开更多
为克服传统正交小波变换盲均衡算法(Wavelet transform constant modulus blind equalization algorithm,WTCMA)收敛速度慢、均方误差大、易于陷入局部极小值的缺点,提出了一种基于DNA遗传优化的正交小波常模盲均衡算法(Wavelet transfo...为克服传统正交小波变换盲均衡算法(Wavelet transform constant modulus blind equalization algorithm,WTCMA)收敛速度慢、均方误差大、易于陷入局部极小值的缺点,提出了一种基于DNA遗传优化的正交小波常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of DNA genetic algorithm,DNA-GA-WTCMA)。该算法采用基于DNA核苷酸链的编码方式表示问题的可能解,并且对编码后的DNA链采用新型的交叉操作和变异操作来寻找DNA种群中的最优个体,然后将得到的最优个体进行解码,把解码后得到的权向量作为均衡器的最优权向量,以避免WTCMA出现局部收敛并提高收敛速度。仿真实验表明,与基于遗传优化的正交小波变换常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of genetic algorithm,GA-WTCMA)相比,该算法可以获得更快的收敛速度和更低的均方误差。展开更多
基金funded by United Arab Emirates University(UAEU)under the UAEU-AUA grant number G00004577(12N145)with the corresponding grant at Universiti Malaya(UM)under grant number IF019-2024.
文摘Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core.To address this limitation,this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer(PKO),a nature-inspired algorithm,to enhance the accuracy of shear strength prediction for CFST columns.Additionally,quantile regression is employed to construct prediction intervals for the ultimate shear force,while the Asymmetric Squared Error Loss(ASEL)function is incorporated to mitigate overestimation errors.The computational results demonstrate that the PKO-XGBoost model delivers superior predictive accuracy,achieving a Mean Absolute Percentage Error(MAPE)of 4.431%and R2 of 0.9925 on the test set.Furthermore,the ASEL-PKO-XGBoost model substantially reduces overestimation errors to 28.26%,with negligible impact on predictive performance.Additionally,based on the Genetic Algorithm(GA)and existing equation models,a strength equation model is developed,achieving markedly higher accuracy than existing models(R^(2)=0.934).Lastly,web-based Graphical User Interfaces(GUIs)were developed to enable real-time prediction.
文摘为克服传统正交小波变换盲均衡算法(Wavelet transform constant modulus blind equalization algorithm,WTCMA)收敛速度慢、均方误差大、易于陷入局部极小值的缺点,提出了一种基于DNA遗传优化的正交小波常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of DNA genetic algorithm,DNA-GA-WTCMA)。该算法采用基于DNA核苷酸链的编码方式表示问题的可能解,并且对编码后的DNA链采用新型的交叉操作和变异操作来寻找DNA种群中的最优个体,然后将得到的最优个体进行解码,把解码后得到的权向量作为均衡器的最优权向量,以避免WTCMA出现局部收敛并提高收敛速度。仿真实验表明,与基于遗传优化的正交小波变换常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of genetic algorithm,GA-WTCMA)相比,该算法可以获得更快的收敛速度和更低的均方误差。
