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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。
Based on the brief introduction of neural network clustering and identification principle, this paper applied the research on the roof clustering and identification of mining face, and the positive utilization rate of clustering and identification reached 100%. The examples show that the neural network is an effective method for clustering and identification of complex nonlinear systems and is expected to be applied to other clustering and identification problems in the field of coal mining.