Prediction Of Vertical Bearing Capacity Of Single Pile Using Neural Networks

this paper has introduced essential concept of Artificial neural network, summarized basal theory of multilayer back- propagation network, put stress on expounding some issue on multilayer back- propagation network in practice, demonstrated the feasibility of resolving pile engineer with Artificial neural network, discussed primary problems about some method and research of characteristic analysis on pile engineer these days, and analyzed data on test of single pile. It has been established the BP Artificial neural network model that five parameters such as the length of pile, the diameter of pile, the depth of pile embedding soil, weighted average of side resistance of friction, and bearing capacity of pile end are import cell, there is one middle layer, 2N+1 artificial neural cells of middle layer, and one export layer that is single pile Vertical bearing capacity. Thirty roots of precast reinforced concrete piles and bored and cast-in-place piles in xi'an had been trained with this model, and nine roots of precast reinforced concrete piles and eight roots of cast-in-place piles had been predicted by simulating. When contrasted and analyzed the predicting result and actual numerical value, the error is always less than 20%(mostly within 15%), which has achieved a better result.