现代矿业 ›› 2013, Vol. 29 ›› Issue (01): 21-23.
• 采选工程 • 上一篇 下一篇
潘勇1,杨天祥2
出版日期:
发布日期:
Pan Yong1,Yang Tianxiang2
Online:
Published:
摘要: 以神经网络技术为基础,利用MATLAB软件设计了岩体可爆性分级的BP神经网络判别模型,使用此模型完成对某铁矿中7种不同岩体岩体可爆性分级判别,并将此判别结果与使用模糊识别方法的判别结果进行比较分析,得出的结论一致。体现了使用MATLAB语言设计BP神经网络模型不仅简便精确,而且还具备较强的可行性和客观性。
关键词: 岩体, 神经网络, 可爆性分级
Abstract: Based on neural network technology, BP neural network discriminant model of rock blasting classification was designed by using MATLAB software.Rock blasting classification discriminant of 7 different kinds of rock in a iron mine were done by using this model.Comparative analysis was done between this discriminant results and discriminant results by fuzzy identification method, the conclusions were the same.Meanwhile, it shows BP neural network model designed by using MATLAB language has characteristics of simple and accurate, and it also has high feasibility and objectivity.
Key words: Rock mass, Neural network, Blastability classification
潘勇, 杨天祥. 岩体可爆性分级的神经网络判别方法[J]. 现代矿业, 2013, 29(01): 21-23.
PAN Yong, YANG Tian-Xiang. Neural Network Discriminant Method of Rock Blasting Classification[J]. Modern Mining, 2013, 29(01): 21-23.
0 / / 推荐
导出引用管理器 EndNote|Ris|BibTeX
链接本文: http://www.xdky.net/CN/
http://www.xdky.net/CN/Y2013/V29/I01/21