摘要
采用人工神经网络和非线性回归方法研究岩爆判据研究。首先利用人工神经网络对原始样本进行量化,然后对量化后的样本数据进行非线性回归分析,获得新的岩爆判据公式。研究结果表明:此岩爆判据公式具有较高的预测精度。
Rockburst criterion was studied based on artificial neural networks and nonlinear regression,Firstly the original sample was quantified by artificial neural networks,and then the nonlinear regression method was used to analyze the quantitative sample data.Finally,the new rockburst criterion was obtained.The results show that the new rockbust criterion has a higher predictive precision.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第7期2977-2981,共5页
Journal of Central South University:Science and Technology
基金
国家高技术研究发展计划("863"计划)项目(2008AA062104)
国家重点基础研究发展计划("973"计划)项目(2010CB731501)
"十一五"国家科技支撑计划项目(2008BAB32B01)
河北省钢铁产业技术升级专项资金资助项目(SJGS-KJ-12-03)
关键词
岩爆判据
人工神经网络
岩爆强度衡量值
非线性回归
rockburst criterion
artificial neural networks
measurable value of rockburst
nonlinear regression
