摘要
在分析各种导水裂隙带高度影响因素的基础上,利用粗糙集理论约简得到最佳的元素集合,将其作为神经网络的输入层,建立基于粗糙集理论的导水裂隙带高度预计神经网络模型,并结合实测数据,检验模型的精度。
Based on the analysis of the influencing factors of various fissure zone height, the optimal set of elements is obtained by rough set theory. Put the set as the input layer of the neural network to establish the prediction model, then the accuracy of the model is verified by the measured data.
作者
孟彦杰
査剑锋
MENG Yan-jie1, ZHA Jian-feng1,2(1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China; 2. NASG Key Lab for Land Environment and Disaster Monitoring, Xuzhou 221116, Chin)
出处
《煤炭技术》
CAS
2018年第4期166-167,共2页
Coal Technology
关键词
粗糙集理论
导水裂隙带高度
BP神经网络
rough set theory
development height of water flowing fractured zone
BP neural network
