Prediction of Bearing Capacity of Composite Foundation of Vibrating Gravel Pile Based on RBF Neural Network

EasyChair Preprint no. 1310, version 1

Abstract

Because many factors related to the bearing capacity of composite foundation of vibrating gravel piles interact with each other, it is difficult to accurately calculate the bearing capacity of foundation. At present, the accurate load test method for bearing capacity of composite foundation requires a lot of manpower and resources and takes a long time, so it may not meet the demand of the real-time detection of on-site construction quality and the progress of project. In this paper, a prediction model of bearing capacity of composite foundation based on RBF neural network is established, and it is compared with the same model based on BP neural network. The prediction results of two models show that the method of predicting the bearing capacity of the composite foundation of the vibrating gravel pile based on RBF neural network is more accurate than that based on BP neural network, and it takes less time to compute, which provides a new artificial intelligence solution for the rapid design of verification for bearing capacity of composite foundation of vibrating gravel pile.

Keyphrases: bearing capacity of composite foundation, BP neural network, RBF neural network

@Booklet{EasyChair:1310,
  author = {Wei Wei and Haiyan Xie and Xinxin Mao and He Hu},
  title = {Prediction of Bearing Capacity of Composite Foundation of Vibrating Gravel Pile Based on RBF Neural Network},
  howpublished = {EasyChair Preprint no. 1310},

  year = {EasyChair, 2019}}