摘要
采煤机煤岩界面识别技术是实现采煤工作面自动化的关键技术之一。利用自组织竞争神经网络对采煤机煤岩界面模式识别进行仿真分析,结果表明,自组织竞争神经网络能对输入向量模式进行正确分类,并能很好地解决采煤机煤岩界面模式识别问题,从而为采煤机煤岩模式识别器的改进提供了技术参考。
Coal-rock interface recognition of shearer is one of the key techniques for automation on working faces. Self-organizing competitive neural network was applied to simulate coal-rock interface pattern recognition. Simulation results show that self-organizing competitive neural network can successfully solve coal-rock interface pattern recognition, which offers technical references for improvement of coal-rock interface pattern recognizer of shearer.
出处
《矿山机械》
北大核心
2010年第15期27-30,共4页
Mining & Processing Equipment
基金
国家863重点项目(2008AA062202)
关键词
采煤机
自组织竞争神经网络
模式识别
煤岩界面
shearer
self-organizing competitive neural network
pattern recognition
coal-rock interface
