Application research of neural networks to geotechnical engineering has become a hotspot nowadays. General model may not reach the predicting precision in practical application due to different characteristics in different fields. In allusion to this, an elasto-plastic constitutive model based on clustering radial basis function neural network(BC-RBFNN) was proposed for moderate sandy clay according to its properties. Firstly, knowledge base was established on triaxial compression testing data; then the model was trained, learned and emulated using knowledge base; finally, predicting results o...
