With the rising needs of better prediction of the load-displacement performance of grouted anchors in an era of developing large-scale underground infrastructures,the existing methods in literature lack an accurate an...With the rising needs of better prediction of the load-displacement performance of grouted anchors in an era of developing large-scale underground infrastructures,the existing methods in literature lack an accurate analytical model for the real-life projects or rigorous understanding of the parameters such as grouting pressures.This paper proposes Fast ICA-MARS as a novel data-driven approach for the prediction of the load-displacement performance of uplift-resisting grouted anchors.The hybrid and data-driven Fast ICA-MARS approach integrates the multivariate adaptive regression splines(MARS)technique with the Fast ICA algorithm which is for Independent Component Analysis(ICA).A database of 4315 observations for 479 different anchors from 7 different projects is established.The database is then used to train,validate and compare the Fast ICA-MARS approach with the classical MARS approach.The developed Fast ICA-MARS model can provide more accurate predictions than MARS.Moreover,the developed Fast ICA-MARS model is easy to interpret since the evaluation of the parameter importance of the independent components can be conducted along with the considerations of the correlations with the original variables.It is noteworthy to point out that the grouting pressures play a central role in the proposed model,which is considered of paramount importance in engineering practices but has not been properly taken into account in any prior analytical or empirical predictive models for the load-displacement relationships.展开更多
基金support from the China Postdoctoral Science Foundation(Grant No.2019M663113)the National Key R&D Program of China(No.2019YFB2102703)。
文摘With the rising needs of better prediction of the load-displacement performance of grouted anchors in an era of developing large-scale underground infrastructures,the existing methods in literature lack an accurate analytical model for the real-life projects or rigorous understanding of the parameters such as grouting pressures.This paper proposes Fast ICA-MARS as a novel data-driven approach for the prediction of the load-displacement performance of uplift-resisting grouted anchors.The hybrid and data-driven Fast ICA-MARS approach integrates the multivariate adaptive regression splines(MARS)technique with the Fast ICA algorithm which is for Independent Component Analysis(ICA).A database of 4315 observations for 479 different anchors from 7 different projects is established.The database is then used to train,validate and compare the Fast ICA-MARS approach with the classical MARS approach.The developed Fast ICA-MARS model can provide more accurate predictions than MARS.Moreover,the developed Fast ICA-MARS model is easy to interpret since the evaluation of the parameter importance of the independent components can be conducted along with the considerations of the correlations with the original variables.It is noteworthy to point out that the grouting pressures play a central role in the proposed model,which is considered of paramount importance in engineering practices but has not been properly taken into account in any prior analytical or empirical predictive models for the load-displacement relationships.
