摘要
本文在神经网络聚类与辨识原理简介的基础上，时采面顶板聚类与辨识问题进行了应用研究，其聚类及辨识的正用率达１００％。实例表明，神经网络是用于复杂非线性系统聚类与辨识的有效方法，并可望在煤矿开采领域其它聚类及辨识问题中得以推广应用。
On the basis of simply introducing the principle of cluster and identification ofArtificial Netiral Network(ANN),this paper focuses on the cluster and identification of coal-face roof, the accuracy of the cluster and identification can reach to 100%. Results shown that the ANN is an effective methods for the cluster and identification of complicated non-linear system.And it has a good prospect for solving other cluster and identification problemsin the field of mining.
出处
《山东矿业学院学报》
CAS
1995年第1期78-82,共5页
Journal of Shandong University of Science and Technology(Natural Science)
关键词
神经网络
聚类
辨识
采面顶板
矿井
Artificial Neural Network(ANN)
cluster and identification
coal-face roof
