西安科技大学学报2012，Vol.32Issue(2)：234-238,258,6.
基于BP神经网络的空洞型采空区稳定性评价研究
Stability evaluation of empty mine goaf based on BP neural network
唐胜利 1唐皓 2郭辉3
作者信息
- 1. 西安科技大学地质与环境学院,陕西西安710054
- 2. 长安大学地质工程与测绘学院,陕西西安710054
- 3. 中国煤炭科工集团西安研究院,陕西西安710054
- 折叠
摘要
Abstract
A BP neural network model for evaluation of stability of empty mine goaf was built based on the theory of BP neural network through analysis on the influence factors of empty mine goaf. The BP neural network model was trained by collected samples of empty mine goaf and the logical parameters of BP neural network were acquired and tested by the testing samples for accuracy. Taking Taolaowusu mine goaf as an example, through evaluating its stability with the trained BP neural network, the result identical with actual situation was got.关键词
空洞型/采空区/BP神经网络/稳定性/评价Key words
empty/ mine goaf/ BP neural network/ stability evaluation分类
矿业与冶金引用本文复制引用
唐胜利,唐皓,郭辉..基于BP神经网络的空洞型采空区稳定性评价研究[J].西安科技大学学报,2012,32(2):234-238,258,6.
