Prediction of rockburst by genetic algorithm-neural network

YIN Guang-zhi; DAI Gao-fei; YAN He; WEI Zuo-an

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Prediction of rockburst by genetic algorithm-neural network

更新时间：2026-06-25

- Prediction of rockburst by genetic algorithm-neural network
- Vol. 24, Issue 6, (2003)
- 作者机构：
  
  1. 重庆大学西南资源开发及环境灾害控制工程教育部重点实验室,重庆,400044
  2. 重庆大学资源及环境科学学院,重庆,400044
  3. 同济大学地下建筑与工程系,上海,200092
- 作者简介：
- 基金信息：
- DOI：
  CLC： TD265
- Online First：19 August 2014，
  
  Published：2003
- 稿件说明：
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YIN Guang-zhi, DAI Gao-fei, YAN He, et al. Prediction of rockburst by genetic algorithm-neural network[J]. 2003, 24(6).
DOI：

YIN Guang-zhi, DAI Gao-fei, YAN He, et al. Prediction of rockburst by genetic algorithm-neural network[J]. 2003, 24(6). DOI：

摘要

根据重庆市南桐矿务局砚石台煤矿的生产技术条件和开采地质条件，针对传统方法预测冲击地压存在的弊端，运用BP人工神经网络和遗传算法相结合的方法，通过改进激励函数来缩短训练时间，并利用给权值加入动量项和变速率学习方法，减少学习中的振荡，来对该矿冲击地压预测进行研究。工程实际应用表明，该方法能有效的确定网络结构和训练参数，并可以很好地应用在相关工程上。

Abstract

Based on the research of mining circumstances and geological conditions of rockburst in Yanshitai coal mine

the influence factors of rockburst are provided. Because of the shortage of traditional methods to forecast rockburst

the method based on the back propagation neural network and genetic algorithm is applied to predict rockburst through reduction training time and instability in network training in Yanshitai coal mine. The results show that it is an effective method to predict rockburst and it can be applied to similar engineerings.

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