Pile-soil interaction prediction analysis method based on machine learning

A machine learning and predictive analysis technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as low efficiency and high cost, and achieve the effect of accurate prediction, low efficiency and clear process.

Active Publication Date: 2020-05-29
SOUTHWEST JIAOTONG UNIV
View PDF6 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art, to provide a fast and accurate pile-soil interaction prediction analysis method based on machine learning, to find out the stress and deformatio

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pile-soil interaction prediction analysis method based on machine learning
  • Pile-soil interaction prediction analysis method based on machine learning
  • Pile-soil interaction prediction analysis method based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0023] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. The technical solutions and technical features provided in each part of the present invention, including the following description, can be combined with each other under the condition of no conflict. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.

[0024] Such as figure 2 As shown, the present invention provides a technical solution: a method for predicting and analyzing pile-soil interaction based on machine learning, comprising the following steps:

[0025] S1. Using the Latin hypercube sampling method to establish a parameter sample of the pile-soil variable to make the sam...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a pile-soil interaction prediction analysis method based on machine learning, and belongs to the technical field of foundation engineering. The method comprises the following steps: establishing a pile-soil variable parameter sample by adopting a Latin hypercube sampling method, modeling the parameter sample by adopting a numerical simulation method to obtain a stress deformation value of a pile body corresponding to the parameter sample, and performing sensitivity analysis on an input variable and a demand variable by adopting a Lasso method to reduce the dimension ofthe input variable; dividing the parameter samples into K parts with equal quantity for cross validation; establishing a BP neural network model based on an L-M algorithm, defining the number of neurons of the hidden layer within a certain range for cyclic traversal operation, determining the optimal number of neurons of the hidden layer by comparing training errors, and predicting the stress deformation of the pile body by using the trained neural network model. The method has the advantages of being clear in analysis process, high in reliability and high in efficiency, and a theoretical basis is provided for design and application of the pile foundation.

Description

technical field [0001] The invention relates to a method for predicting and analyzing pile-soil interaction based on machine learning, which belongs to the technical field of foundation engineering. Background technique [0002] Pile foundations are widely used in various engineering constructions, and are the most commonly used treatment methods for bad foundations. With the development of pile foundation technology, some new pile foundation technologies have appeared, such as spiral steel pile, composite geotechnical material encapsulated bulk pile, etc. There are many factors influencing the design of these piles. Understanding its stress and deformation characteristics is of great significance to the safety, stability and economy of the project. The bearing capacity of the pile foundation is the result of the joint action of the pile and the soil. The traditional field load test is the most commonly used analysis method. By analyzing the bearing capacity of a single pil...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F30/23G06F30/27G06F30/13G06N3/04G06N3/08G06F119/14
CPCG06N3/084G06N3/048G06N3/045
Inventor 刘凯文邱睿哲何川倪芃芃梅国雄陈德苏谦黄俊杰越斐周鹏飞熊志鹏李源港邵康牛妤冰
Owner SOUTHWEST JIAOTONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products