| The risk early-warning of gas hazard in coal mine based on Rough Set-neural network |
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| 作者姓名： | 田水承 王莉 |
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| 作者单位： | School of Energy, Xi＇an University of Science ＆ Technology, Xi＇an 710054, China |
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| 基金项目： | Supported by National Natural Science Fund of China（70673079）; Natural Science Fund of Shannxi（2001 C38）; Education Committee Science Fund of Shannxi （00JK214） |
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| 摘 要： | This article proposed the risk early-warning model of gas hazard based on Rough Set and neural network. The attribute quantity was reduced by Rough Set, the main characteristic attributes were withdrawn, the complexity of neural network system and the computing time was reduced, as well. Because of fault-tolerant ability, parallel processing ability, anti-jamming ability and processing non-linear problem ability of neural network system, the methods of Rough Set and neural network were combined. The examples research indicate： applying Rough Set and BP neural network to the gas hazard risk early-warning coal mines in coal mine, the BPNN structure is greatly simplified, the network computation quantity is reduced and the convergence rate is speed up.
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| 关 键 词： | 神经网络 报警 天然气 煤矿 |
The risk early-warning of gas hazard in coal mine based on Rough Set-neural network |
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| TIAN Shui-cheng, WANG Li.The risk early-warning of gas hazard in coal mine based on Rough Set-neural network[J].Journal of Coal Science & Engineering(China),2007,13(4):400-404. |
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| Authors: | TIAN Shui-cheng WANG Li |
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