|本期目录/Table of Contents|

[1]朱志洁,张宏伟.基于GA-ELM的冲击地压危险性预测研究[J].中国安全生产科学技术,2014,10(8):46-51.[doi:10.11731/j.issn.1673-193x.2014.08.008]
　ZHU Zhi-jie,ZHANG Hong-wei.Study on hazard prediction of rock burst based on GA-ELM[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2014,10(8):46-51.[doi:10.11731/j.issn.1673-193x.2014.08.008]
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基于GA-ELM的冲击地压危险性预测研究
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
10
期数:
2014年8期
页码:
46-51
栏目:
学术论著
出版日期:
2014-08-31

文章信息/Info

Title:
Study on hazard prediction of rock burst based on GA-ELM
作者:
朱志洁; 张宏伟
(辽宁工程技术大学 矿业学院，辽宁 阜新 123000)
Author(s):
ZHU Zhi-jie;  ZHANG Hong-wei
(College ofmining engineering, Liaoning Technical University, Fuxin Liaoning 123000, China)
关键词:
冲击地压; 遗传算法（GA）; 极限学习机（ELM）; 仿真预测
Keywords:
rock burst;  genetic algorithms(GA);  extreme learning machine (ELM);  simulation and prediction
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2014.08.008
文献标志码:
A
摘要:
为提高冲击地压预测的效率和准确率，在分析冲击地压影响因素的基础上，提出了一种将遗传算法(GA)与极限学习机(ELM)相结合的冲击地压预测的新方法。为了避免ELM受输入权值矩阵和隐含层偏差随机性的影响，算法采用GA对ELM的输入权值矩阵和隐含层偏差进行优化，建立GA-ELM冲击地压预测模型。利用某矿冲击地压统计数据对该模型进行了实例分析，将ELM、SVM和BP算法预测结果与该模型进行了对比分析。结果表明：GA-ELM模型具有较高的预测精度，可以相对准确、有效地对冲击地压发生的可能性进行预测。
Abstract:
In order to improve the efficiency and accuracy of rock burst prediction, a new method combining extreme learning machine (ELM) and genetic algorithm (GA) for rock burst prediction was proposed based on analyzing the influencing factors of rock burst. In order to avoid the influence on predicting effect of ELM by the randomness of input weight matrix and hidden layer deviation, GA was used to optimize the input weight matrix and hidden layer deviation, and the GAELM model for rock burst prediction was built. Case analysis was made using statistical data of a coal mine, and the prediction result was compared with ELM, SVM and BP. The results showed that the prediction on possibility of rock burst by GAELM model can be relatively accurate and effective.

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备注/Memo

备注/Memo:
国家自然科学基金项目(51274117)
更新日期/Last Update: 2014-09-26