| 神经网络在综放回采巷道锚杆支护设计中的应用研究 |
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| 引用本文： | 周保生,朱维申,李术才.神经网络在综放回采巷道锚杆支护设计中的应用研究[J].岩石力学与工程学报,2001,20(4):497-501. |
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| 作者姓名： | 周保生 朱维申 李术才 |
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| 作者单位： | 1. 深圳市天健集团股份有限公司,深圳,518034
2. 中国科学院武汉岩土力学研究所,武汉,430071 |
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| 摘 要： | 针对传统的BP网络学习算法的缺陷，研究一种动态学习算法。依据人工神经网络的一般原理，利用网络的非线性映射功能，实现了综放回采巷道的锚杆支护设计。结果表明，网络的设计结果与现场实际吻合很好。
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| 关 键 词： | 回采巷道 神经网络 锚杆 支护 设计 |
| 文章编号： | 1000-6915(2001)04-0497-05 |
| 修稿时间： | 1999年12月16 |
USING NEURAL NETWORK ON BOLTING SUPPORT DESIGN OF MINING ROADWAY FOR FULLY MECHANIZED WORKING FACE WITH TOP-COAL CAVING |
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| Zhou Baosheng,Zhu Weishen,Li Shucai.USING NEURAL NETWORK ON BOLTING SUPPORT DESIGN OF MINING ROADWAY FOR FULLY MECHANIZED WORKING FACE WITH TOP-COAL CAVING[J].Chinese Journal of Rock Mechanics and Engineering,2001,20(4):497-501. |
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| Authors: | Zhou Baosheng Zhu Weishen Li Shucai |
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| Abstract: | A new dynamic learning algorithm is proposed to overcome the shortcoming of traditional BP net learning algorithm. Based on the principle of artificial neural network and the proposed algorithm, the bolt support design of mining roadway is made for fully mechanized working face with top-coal caving, and the results keep coincidence well with practical case. |
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| Keywords: | fully mechanized working face with top-coal caving mining roadway neural network bolt support design |
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