基于BP神经网络的深基坑支护结构选型研究

here are numerous factors to affect protecting architecture of deep foundation excavation, they have the relation with nonlinear. This paper apply Neural Network which have the characteristic of solve high nonlinear problem ,through founding BP Neural Network model and training for plenty of successful project examples , establishes nonlinear mapping relation between many input of influence factors and unitary export of protecting architecture form. At last we can get the optimize protecting architecture form. This model tested by test data, has been proven that it is reasonably feasible.