言语产生是一项高度复杂的感觉运动任务,在言语产生过程中,运动编程将抽象的语音代码转化为特定的运动指令,一直被认为是一个关键步骤。运动编程在理解言语失用症(apraxia of speech)具有特殊的相关性。言语失用症是一种运动语音障碍,...言语产生是一项高度复杂的感觉运动任务,在言语产生过程中,运动编程将抽象的语音代码转化为特定的运动指令,一直被认为是一个关键步骤。运动编程在理解言语失用症(apraxia of speech)具有特殊的相关性。言语失用症是一种运动语音障碍,它的特点是在言语产生的层级加工过程中,发音和韵律的破坏[1]。近几十年,由于神经成像和计算方法的出现,促进了言语运动编程和执行的神经计算模型的开发。在当前,具有生物学意义的言语生成和获得神经网络模型中。展开更多
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
文摘言语产生是一项高度复杂的感觉运动任务,在言语产生过程中,运动编程将抽象的语音代码转化为特定的运动指令,一直被认为是一个关键步骤。运动编程在理解言语失用症(apraxia of speech)具有特殊的相关性。言语失用症是一种运动语音障碍,它的特点是在言语产生的层级加工过程中,发音和韵律的破坏[1]。近几十年,由于神经成像和计算方法的出现,促进了言语运动编程和执行的神经计算模型的开发。在当前,具有生物学意义的言语生成和获得神经网络模型中。
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.
