This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-E...This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R^2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.展开更多
The problem of constructing a model dimensional parabolic system is considered in this reference adaptive control law for an uncertain 1- article. The controller designed here involves only the plant state but no its ...The problem of constructing a model dimensional parabolic system is considered in this reference adaptive control law for an uncertain 1- article. The controller designed here involves only the plant state but no its derivatives. A priori bounds on the plant＇s uncertain parameters are used to propose switching laws which serve as an adaptive mechanism. The exponential decay to zero of the state error with any prescribed rate is guaranteed by choosing a controller parameter correspondingly. Numerical studies are also presented to illustrate the applicability of the control law.展开更多
文摘This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R^2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.
基金supported by State Scholarship Fund of China under Grant No.2010602510 from China Scholarship Council(CSC)the National Natural Science Foundation of China under Grant No.11101082+2 种基金the National Natural Science Foundation of China under Grant Nos.10626002,61374088 and 71371024the Program for Innovative Research Team in UIBEthe research foundation of University of International Business and Economics under Grant No.7500010336
文摘The problem of constructing a model dimensional parabolic system is considered in this reference adaptive control law for an uncertain 1- article. The controller designed here involves only the plant state but no its derivatives. A priori bounds on the plant＇s uncertain parameters are used to propose switching laws which serve as an adaptive mechanism. The exponential decay to zero of the state error with any prescribed rate is guaranteed by choosing a controller parameter correspondingly. Numerical studies are also presented to illustrate the applicability of the control law.
