PREDICTION OF TBM JAMMING RISK IN SQUEEZING GROUNDS USING BAYESIAN AND ARTIFICIAL NEURAL NETWORKS

2014 dodge ram 1500 fender flares This study presents an application of artificial neural network (ANN) and Bayesian network (BN) for evaluation of jamming risk of the shielded tunnel boring machines (TBMs) in adverse ground conditions such as squeezing grounds.The analysis is based on database of tunneling cases by numerical modeling to evaluate t

Abstract Background The microtubule-dependent molecular motor protein Kinesin Family Member 2A (KIF2A) is down-regulated in asthmatic human airway epithelium.However, little is known about the roles of KIF2A as well as the possible underlying mechanisms in asthma.Methods House dust mite (HDM) extract was administered to establish a murine model of