| 煤层底板突水组合人工神经网络预测 |
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| 引用本文： | 王连国,宋扬. 煤层底板突水组合人工神经网络预测[J]. 岩土工程学报, 2001, 23(4): 502-505 |
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| 作者姓名： | 王连国 宋扬 |
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| 作者单位： | 山东科技大学土木建筑学院!山东泰安271019；山东科技大学资源与环境工程学院!山东泰安271019； |
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| 摘 要： | 综合考虑水源、水压、隔水层、断层等因素对煤层底板突水的影响 ,采用遗传算法训练人工神经网络 ,建立了煤层底板突水组合人工神经网络预测模型。实例分析表明 ,采用遗传算法训练BP网络明显提高了人工神经网络的预测精度 ,使预测结果更加可靠
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| 关 键 词： | 煤层底板 突水 人工神经网络 遗传算法 预测 |
| 文章编号： | 1000-4548(2001)04-0502-04 |
| 修稿时间： | 2000-11-02 |
Combined ANN forecast of water-inrush from coal floor |
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| WANG Lianguo,SONG Yang. Combined ANN forecast of water-inrush from coal floor[J]. Chinese Journal of Geotechnical Engineering, 2001, 23(4): 502-505 |
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| Authors: | WANG Lianguo SONG Yang |
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| Affiliation: | 1.Institute of Civil and Architecture Engineering Shandong University of Science and Technology Tai’an 271019 China 2.Institute of Resource and Environmental Engineering Shandong University of Science and Technology Tai’an |
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| Abstract: | This paper considers comprehensively water source, water pressure,water impedance strata, and fault etc to establish a combined ANN forecast model of water inrush from coal floor by using genetic algorithms to train ANN. The analysis of actual examples indicates the forecast precision of ANN trained by genetic algorithms is obviously enhanced, so that it makes the predicted result more reliable. |
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| Keywords: | coal floor water inrush ANN genetic algorithms forecast |
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