期刊
ARABIAN JOURNAL OF GEOSCIENCES
卷 8, 期 6, 页码 4269-4278出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12517-014-1477-9
关键词
Blasting; Ground vibrations; Rock properties; Artificial neural networks
资金
- Scientific and Technological Research Council of Turkey (TUBITAK) [110M294]
This study addresses the effects of rock characteristics and blasting design parameters on blast-induced vibrations in the Kangal open-pit coal mine, the Tulu open-pit boron mine, and the Kirka open-pit boron mine. In this study, multiple vibration measurements have been conducted, and the related data have been analyzed and evaluated. Several artificial neural network (ANN) and regression models based on the same blasting design parameters, resistivity, and P-wave and S wave velocities of the surrounding rocks have been constructed to estimate the peak particle velocities and the frequencies of related blast-induced vibrations. The data derived from these models and the classical evaluations indicate that ANNs provide more reliable results than the other methods.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据