Recognition of collapse type of surrounding rock mass based on support vector machine

ZHAO Hong-bo

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Recognition of collapse type of surrounding rock mass based on support vector machine

更新时间：2026-06-25

- Recognition of collapse type of surrounding rock mass based on support vector machine
- Vol. 26, Issue 2期　刊出日, (2005)
- 作者机构：
  
  1. 浙江大学建筑工程学院,浙江,杭州,310027
  2. 绍兴文理学院土木系,浙江,绍兴,312000
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU452
- Online First：19 November 2013，
  
  Published：2005
- 稿件说明：
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ZHAO Hong-bo. Recognition of collapse type of surrounding rock mass based on support vector machine[J]. 2005, 26(2期　刊出日).
DOI：

ZHAO Hong-bo. Recognition of collapse type of surrounding rock mass based on support vector machine[J]. 2005, 26(2期　刊出日). DOI：

摘要

围岩的破坏受到多种因素的影响，并且各破坏模式之间没有明显的界限，因此其破坏模式的识别是一种模糊、非线性、小样本、高维数的模式识别问题。支持向量机（SVM）是最近发展起来的一种新机器学习技术，已在模式识别领域有很多成功地应用。基于支持向量机的思想，提出了围岩破坏模式识别的支持向量机方法，很好地表达了围岩破坏模式与其影响因素之间的复杂非线性关系。具体算例表明，该方法是可行的，具有一定的准确性。

Abstract

The collapse of surrounding rock mass is affected by many factors

and the relationship between different collapse types has no distinct boundary

so the problem of recognition of collapse type is fuzzy

nonlinear

small samples and high dimensions. Support vector machine is a new machine learning technology

and there are a lot of successful application in the field of pattern recognition. This paper presents a new method based on support vector machine

and the complicated nonlinear relationship between type of collapse and its affected actors is presented well. The application of true example shows this method is feasible and precise.

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Related Institution

Key Laboratory of Rock and Soil Mechanics, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences

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