基于SVM的冲击地压分级预测模型及R语言实现

张曼; 陈建宏; 周智勇

doi:10.13225/j.cnki.jccs.2008.08.007

基于SVM的冲击地压分级预测模型及R语言实现

(中南大学资源与安全工程学院,长沙,410083)

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出版历程
- 刊出日期: 2018-08-24

Grading Prediction Model of Rock Burst Based on SVM and Realization of R Language

(School of Resource and Safety Engineering, Central South University, Changsha 410083)

摘要

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。
- 冲击地压 /
- 支持向量机 /
- R语言 /
- 分层随机抽样

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参考文献(18)

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