[1]张曼,陈建宏,周智勇,等.基于SVM的冲击地压分级预测模型及R语言实现[J].中国地质灾害与防治学报,2018,29(4):64-69.[doi:10.13225/j.cnki.jccs.2008.08.007]
 ZHANG MAN,CHEN JIANHONG,ZHOU Zhiyong,et al.Grading Prediction Model of Rock Burst Based on SVM and Realization of R Language[J].The Chinese Journal of Geological Hazard and control,2018,29(4):64-69.[doi:10.13225/j.cnki.jccs.2008.08.007]
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基于SVM的冲击地压分级预测模型及R语言实现()
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《中国地质灾害与防治学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2018年4
页码:
64-69
栏目:
出版日期:
2018-08-25

文章信息/Info

Title:
Grading Prediction Model of Rock Burst Based on SVM and Realization of R Language
作者:
 张曼; 陈建宏; 周智勇;
(中南大学资源与安全工程学院,长沙,410083)
Author(s):
ZHANG MAN CHEN JIANHONGZHOU Zhiyong;
(School of Resource and Safety Engineering, Central South University, Changsha 410083)
关键词:
冲击地压支持向量机R语言分层随机抽样
分类号:
TD324;X936 文献标示码:A
DOI:
10.13225/j.cnki.jccs.2008.08.007
摘要:
采场冲击地压的分级预测对保障矿山安全具有重要的意义。在综合考虑采场冲击地压等级判别的各类影响因素之后,引入支持向量机理论,建立了采场冲击地压等级判别的SVM模型。通过借助R语言实现了分层随机抽样的技术,保证了训练集与测试集样本数据的随机性和差异性。研究表明:基于SVM理论的采场冲击地压分级预测模型,可靠性强、预测准确率高。同时,采场冲击地压分级预测模型程序化语言的实现,对保障工程后期的研究预测的可持续性具有重大的意义。

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更新日期/Last Update: 2018-09-13