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基于模糊神经网络兖州矿区立井井筒非采动破裂的判别

Judgment for non-mining fracture of shaft-lining in Yanzhou mine based on fuzzy neural network

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【作者】 刘环宇王思敬曾钱帮胡波夏正义

【Author】 LIU Huan-yu1,2,WANG Si-jing3,ZENG Qian-bang3,HU Bo3,XIA Zheng-yi4(1.Institute of Rock and Soil Mechanics,Chinese Academy of Sciences,Wuhan 430071,China;2.SDIC Xinji Energy Co.Ltd,Huainan 232170,China;3.Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China;4.Institute of Logistics Science PLA,Beijing 100071,China)

【机构】 中国科学院武汉岩土力学研究所中国科学院地质与地球物理研究所解放军总后后勤科学研究所 湖北武汉430071国投新集能源股份有限公司安徽淮南232170北京100029北京100071

【摘要】 煤矿立井井筒非采动破裂是一种新型工程地质灾害。该灾害的发生与各影响因素之间的关系为非线性的、不确定的。本文采用模糊神经网络对其中隐藏的规律进行了提取与捕捉。经检验结果表明,通过模糊逻辑判别与人工神经网络的相结合能够很好的对立井井筒破裂灾害的发生进行判别,且结果准确可靠,能够满足实际要求。

【Abstract】 Non-mining fracture of shaft-lining is a new style of engineering geological hazard.The relationship between the developing of fracture and its factors of influence is non-linear and indeterminate.Adopting fuzzy neural network,hidden regularities for non-mining fracture of shaft-lining were extracted and captured.The verifying results indicated that the approach combining fuzzy logical judgment with artificial neural network could distinguish the developing of non-mining fracture of shaft-lining.The obtained results were accurate,reliable and could meet the practical requirements.

【基金】 国家重点基础研究规划(937)资助项目(2002CB12702)
  • 【文献出处】 岩土工程学报 ,Chinese Jounal of Geotechnical Engineering , 编辑部邮箱 ,2005年10期
  • 【分类号】TD321;
  • 【被引频次】16
  • 【下载频次】268
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