| 煤与瓦斯突出的粗神经网络预测模型研究 |
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| 引用本文： | 杨敏,李瑞霞,汪云甲. 煤与瓦斯突出的粗神经网络预测模型研究[J]. 计算机工程与应用, 2010, 46(6): 241-244. DOI: 10.3778/j.issn.1002-8331.2010.06.070 |
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| 作者姓名： | 杨敏 李瑞霞 汪云甲 |
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| 作者单位： | 1.中国矿业大学 环境与测绘学院，江苏 徐州 221008 2.江苏省资源环境信息工程重点实验室，江苏 徐州 221008 3.太原理工大学 阳泉学院，山西 阳泉 045000 |
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| 基金项目： | 国家自然科学基金(No.50534050);;中国矿业大学青年科研基金资助项目(No.2007A033)~~ |
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| 摘 要： | 将粗集方法作为BP神经网络的前端处理器，通过对煤与瓦斯系统属性特征的提取和影响因素的约简，较好解决了预测输入特征的“维数灾”问题，构建了粗集与神经网络相结合的煤与瓦斯突出预测模型。仿真实验表明，验证了该方法的有效性，模型学习速度更快、精确度更高，对提高瓦斯突出预测时效性有重大意义。
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| 关 键 词： | 煤与瓦斯突出预测 粗集 粗神经网络 混合系统 属性约简 |
| 收稿时间： | 2008-08-29 |
| 修稿时间： | 2008-10-21 |
New method for predicting coal or gas outburst based on RSNN neural network |
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| YANG Min,LI Rui-xia,WANG Yun-jia. New method for predicting coal or gas outburst based on RSNN neural network[J]. Computer Engineering and Applications, 2010, 46(6): 241-244. DOI: 10.3778/j.issn.1002-8331.2010.06.070 |
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| Authors: | YANG Min LI Rui-xia WANG Yun-jia |
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| Affiliation: | 1.School of Environment & Spatial Informatics，China University of Mining and Technology，Xuzhou，Jiangsu 221008，China 2.Jiangsu Key Laboratory of Resources and Environmental Information Engineering，CUMT，Xuzhou，Jiangsu 221008，China 3.Yangquan Institute，Taiyuan University of Technology，Yangquan，Shanxi 045000，China |
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| Abstract: | A coal or gas outburst prediction model combining Rough-Set(RS) and BP Artificial Neural Network(ANN) is pre- sented.RS theory is applied in analyzing coal or gas outburst dataset and the dependence relation between geological mining fac- tor and coal or gas outburst is obtained on the basis of these data.So the feature elements are selected from the lager dimen- sions injections and regarded as ANN injection features,the number of the injection features can be reduced,and thedimensions misfortuneproblem ca... |
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| Keywords: | coal or gas outburst prediction rough set rough neural network hybrid systems attribute reduction |
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