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中文摘要：
煤矿瓦斯突出是威胁煤矿安全生产的主要因素之一：瓦斯突出预测的关键是信息的采集,传输和处理;通过DSP技术和粗集-RBF神经网络结合的方法,完成了对瓦斯突出预测系统的设计;该系统设计了基于DSP和无线传感器网络的信息采集和传输系统和粗集-RBF神经网络;信息传输采用无线网络和CAN总线相结合的方式,极大地提高了信息传输的质量和效率;利用MATLAB对粗集-RBF神经网络进行了建模和仿真,选取了4个与瓦斯突出有关的影响指标,对具体的瓦斯突出样本进行了预测,准确预测出了瓦斯突出。
英文摘要：
Coal mine gas outburst is one of the main factors which is a threat to safety production. The key of Gas Outburst prediction is information collection, transmission and proeessing. The design of gas outburst prediction system is completed by the method of combining DSP technology and the rough set;RBF neural network. The system has designed information acquisition and the transmission system based on DSP and the wireless sensor network and the rough set;RBF network. A combination of wireless networks and CAN Bus is used to transmit information, improving the quality and efficiency of information transmission. Using the tool of Matlab in modeling and simulation on rough set＆RBF network. The system predict specific samples of gas outburst and predict gas outburst, selecting four influencing factors.
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