| 煤矿顶板矿压显现实时预报的自适应神经网络方法 |
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| 引用本文： | 冯夏庭,姚建国.煤矿顶板矿压显现实时预报的自适应神经网络方法[J].煤炭学报,1995,20(5):455-460. |
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| 作者姓名： | 冯夏庭 姚建国 |
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| 作者单位： | 东北大学，煤炭科学研究总院北京开采研究所 |
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| 基金项目： | 煤炭科学基金,国家“八五”科技攻关,国家教委博士点基金 |
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| 摘 要： | 应用神经网络系统理论，提出了煤矿顶板压力显现实时预报的自适应模式识别方法。它通过对井下实测压力曲线的记忆，可以预报出该顶板未来的矿压显现规律，包括来压步距来来压强度。实际应用表明，本方法可外推预报１０个工作面推进循环的来压规律，来压强度的预准克达到９３％，来压步距的预准确率为１００％。
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| 关 键 词： | 顶板 实时预报 矿压显现 自适应神经网络 煤矿 |
AN ADAPTIVE NEURAL NETWORK FOR REAL-TIME PREDICTION OF ROCK BEHAVIOUR IN COAL MINES |
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| Feng Xiating, Wang Yongjia.AN ADAPTIVE NEURAL NETWORK FOR REAL-TIME PREDICTION OF ROCK BEHAVIOUR IN COAL MINES[J].Journal of China Coal Society,1995,20(5):455-460. |
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| Authors: | Feng Xiating Wang Yongjia |
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| Abstract: | An adaptive recognition approach for real-time prediction of rock behaviour was proposed by application of artificial neural network theory. It can predict the rules of future rock behaviour including the weighting interval and strength based on output of underground observation data. Practical experience indicates that this method can be applied to prediction of weighting in advancing cycles in ten faces by extrapolation with an accuracy of 93% for weighting strength and 100% for weighting interval. |
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| Keywords: | rock behaviour adaptive pattern recognition real-time prediction |
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