| 基于BP神经网络的孔隙充水矿井涌水量预测 |
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| 引用本文： | 凌成鹏,孙亚军,杨兰和,姜素,邵飞燕.基于BP神经网络的孔隙充水矿井涌水量预测[J].水文地质工程地质,2007,34(5):55-58. |
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| 作者姓名： | 凌成鹏 孙亚军 杨兰和 姜素 邵飞燕 |
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| 作者单位： | 中国矿业大学,徐州,221008 |
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| 基金项目： | 国家自然科学基金;国家重点基础研究发展计划(973计划) |
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| 摘 要： | 文章分析了孔隙充水矿井的充水水源和通道,利用非线性的BP人工神经网络建立了徐州韩桥煤矿涌水量短期预测模型,选取每天的降水量作为影响因子,用已有的涌水量资料训练得到权值和阈值来表示充水通道,并对-200m水平、-270m水平、-330m水平和全矿井涌水量进行了预测。结果显示,涌水量的预测值与实测值吻合得较好,说明该模型具有一定实用性。
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| 关 键 词： | BP人工神经网络 孔隙充水矿井 涌水量 预测模型 韩桥煤矿 |
| 文章编号： | 1000-3665（2007）05-0055-04 |
| 修稿时间： | 2006-11-08 |
Prediction of inrush water of mine with pore water yield based on BP artificial neural network |
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| LING Cheng-peng,SUN Ya-jun,YANG Lan-he,JIANG Su,SHAO Fei-yan.Prediction of inrush water of mine with pore water yield based on BP artificial neural network[J].Hydrogeology and Engineering Geology,2007,34(5):55-58. |
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| Authors: | LING Cheng-peng SUN Ya-jun YANG Lan-he JIANG Su SHAO Fei-yan |
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| Institution: | China University of Mining and Technology, Xuzhou 221008, China |
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| Abstract: | In this paper,sources and channels of water bursting of mine with pore water yield were analyzed and basic theory of artificial neural network was used.The short-time prediction model of mine inrush in the Hanqiao colliery was also established.Daily precipitation within a period of time was chosen as an influence factor.Weight and threshold,which were obtained from training known data of precipitation,were expressed as channels of water inrush.The mine inrush water of-200 m level,-270 m level,-330 m level and the whole mine was predicted.The results show that it is right and feasible to build the BP neural network model and predict mine inrush water. |
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| Keywords: | BP artificial neural network mine with pore water yield mine inrush water prediction model Hanqiao colliery |
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