唐跃,徐曲,柯波,赵明生,柴修伟

• 1:湖北广播电视大学机电工程学院
• 2:湖北省安全生产应急救援中心
• 3:武汉理工大学资源与环境工程学院
• 4:贵州新联爆破工程有限公司

摘要(Abstract)：

为克服传统预测模型凭个人经验随机选择核函数建立SVM的缺陷,基于交叉验证理论,将90个矿岩爆破样本随机切分成10个子集,每次保留其中一个子集作为测试集,迭代训练,通过支持向量机模型参数寻优,得到最优爆破块度预测模型。10次试验结果表明:基于径向基核函数的矿岩爆破块度SVM模型预测性能好,该模型的均方根误差、平均绝对误差的均值分别为0.101、0.0673。同时,基于R语言开发得到了矿岩爆破块度预测模型的程序代码,不仅可以保证预测模型与数据库样本的同步更新,而且为矿岩爆破块度预测模型的可持续性研究提供了技术支持。

关键词(KeyWords)： 爆破块度;交叉验证;支持向量机;随机抽样;模型优选

Abstract:

Keywords:

基金项目(Foundation): 中国博士后科学基金面上项目(2018M632936);; 湖北省教育厅科学技术研究项目(D20171506);; 湖北省安全生产专项资金项目(鄂安监发(2017)35号)

作者(Author): 唐跃,徐曲,柯波,赵明生,柴修伟

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