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| 煤层底板采动导水破坏深度计算的神经网络方法 | |
| 引用本文： | 郭文兵,邹友峰,邓喀中. 煤层底板采动导水破坏深度计算的神经网络方法[J]. 中国安全科学学报, 2003, 13(3): 34-37 |
| 作者姓名： | 郭文兵 邹友峰 邓喀中 |
| 作者单位： | 1. 焦作工学院资源与材料工程系;中国矿业大学环境与测绘学院 2. 焦作工学院资源与材料工程系 3. 中国矿业大学环境与测绘学院 |
| 基金项目： | 河南省自然科学基金资助 (0 3110 5 310 0 ) |
| 摘 要： | 在综合分析影响煤层底板采动导水破坏深度因素的基础上 ,应用人工神经网络方法 ,建立了底板破坏深度的计算模型。该模型利用现场观测资料作为学习训练样本和测试样本 ,对模型的测算结果、理论计算值和实测值进行了对比分析。结果表明 :用神经网络方法计算底板破坏深度考虑的因素更加全面 ,结果更接近于实际。笔者研究的计算模型和测算方法 ,为承压水上安全采煤决策提供了科学依据。 |
| 关 键 词： | 底板破坏深度 人工神经网络 承压水上采煤 |
| 修稿时间： | 2003-07-01 |
Prediction of the Failure Depth of Coal Seam Floor by Artificial Neural Network Method |
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| Guo Wenbing , Assoc. Prof. Zou Youfeng Prof. Deng Kazhong Prof.. Prediction of the Failure Depth of Coal Seam Floor by Artificial Neural Network Method[J]. China Safety Science Journal, 2003, 13(3): 34-37 | |
| Authors: | Guo Wenbing Assoc. Prof. Zou Youfeng Prof. Deng Kazhong Prof. |
| Affiliation: | Guo Wenbing 1,2 Assoc. Prof. Zou Youfeng 1 Prof. Deng Kazhong 2 Prof. |
| Abstract: | Based on the analysis of the factors influencing the failure depth of coal seam floor, a model to predict the failure depth is established by applying the theory of artificial neural network (ANN). A large amount of on-site observed data is used as learning and training samples. Then the predicted results from the model, theoretical results and the observed values are compared and analyzed. The results show that it is more precise to predict the failure depth of coal seam floor by ANN technology. It provides scientific criteria for deciding the mining of the coal over the confined aquifer. |
| Keywords: | Failure depth of coal seam floor Artificial neural networks Coal mining over confined aquifer |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |