| 煤与瓦斯突出的PCA-BP神经网络预测模型研究 |
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| 引用本文： | 许新征,丁世飞,杨胜强,赵作鹏,吴祥.煤与瓦斯突出的PCA-BP神经网络预测模型研究[J].计算机工程与应用,2011,47(28):219-222. |
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| 作者姓名： | 许新征 丁世飞 杨胜强 赵作鹏 吴祥 |
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| 作者单位： | 1.中国矿业大学 计算机科学与技术学院，江苏 徐州 2211162.中国矿业大学 安全工程学院，江苏 徐州 221116 |
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| 基金项目： | 国家自然科学基金(No.60975039); 江苏省基础研究计划(自然科学基金)(No.BK2009093); 中国科学院智能信息处理重点实验室开放基金(No.IIP2010-1); 中国矿业大学青年科研基金项目(No.2008A045)~~ |
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| 摘 要： | 通过主成分分析法对煤与瓦斯突出的主要影响因素进行主成分提取，选取贡献率大于85%的3个主成分来代替原来的7个影响因素，以此来确定BP神经网络的输入参数为3个。根据煤与瓦斯突出的类型，建立了煤与瓦斯突出预测的PCA-BP神经网络模型。选用典型突出矿井的煤与瓦斯突出实例作为学习样本，对PCA-BP网络进行训练。以云南某煤矿的煤与瓦斯突出实例作为预测样本，仿真结果表明PCA-BP神经网络模型性能优于传统BP神经网络，能够满足煤与瓦斯突出预测的要求。
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| 关 键 词： | 主成分分析 神经网络 煤与瓦斯突出 预测 |
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Model for predicting coal and gas outburst based on PCA and BP neural network |
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| XU Xinzheng,DING Shifei,YANG Shengqiang,ZHAO Zuopeng,WU Xiang.Model for predicting coal and gas outburst based on PCA and BP neural network[J].Computer Engineering and Applications,2011,47(28):219-222. |
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| Authors: | XU Xinzheng DING Shifei YANG Shengqiang ZHAO Zuopeng WU Xiang |
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| Affiliation: | 1.School of Computer Science and Technology，China University of Mining and Technology，Xuzhou，Jiangsu 221116，China2.School of Safety Engineering，China University of Mining and Technology，Xuzhou，Jiangsu 221116，China |
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| Abstract: | In this paper,three main factors are extracted to replace seven original factors affecting coal and gas outburst by means of principal component analysis when variance contribution is more than 85%,by which,the input parameters of BP neural network are determined.PCA-BP neural network prediction model is established,which is trained by the study samples from typical coal and gas outburst mines.In order to check feasibility and validity of the PCA-BP model,the instances of a coal mine in Yunnan province are ... |
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| Keywords: | principal component analysis neural network coal and gas outburst forecast
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