| 基于粗糙集和人工神经网络的洞室岩体质量评价 |
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| 引用本文： | 邱道宏,陈剑平,阙金声,安鹏程.基于粗糙集和人工神经网络的洞室岩体质量评价[J].吉林大学学报(地球科学版),2008,38(1):86-91. |
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| 作者姓名： | 邱道宏 陈剑平 阙金声 安鹏程 |
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| 作者单位： | 吉林大学,建设工程学院,长春,130026 |
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| 基金项目： | 国家自然科学基金
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教育部"优秀青年教师资助计划"
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吉林大学校科研和教改项目 |
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| 摘 要： | 针对洞室岩体质量问题,从洞室工程的角度选取能够反映岩体综合工程特性的6个参数,用可拓评判和专家审定的方法构建了决策样本集;再利用粗糙集理论对原始决策样本集进行约简操作,并分析各指标对决策的相对重要性;最后将约简结果生成的规则作为人工神经网络的输入,建立了洞室岩体质量评价模型。通过工程实例分析对比,该模型有效地简化神经网络的网络结构,减少网络的训练步数,提高网络的学习效率,能够较准确地反映洞室岩体的工程特性。
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| 关 键 词： | 岩体质量评价 粗糙集 知识约简 人工神经网络 |
| 文章编号： | 1671-5888（2008）01-0086-06 |
| 收稿时间： | 2007-03-29 |
| 修稿时间： | 2007年3月29日 |
Evaluation of Tunnel Rock Quality with Routh Sets Theory and Artificial Neural Networks |
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| QIU Dao-hong,CHEN Jian-ping,QUE Jin-sheng,AN Peng-cheng.Evaluation of Tunnel Rock Quality with Routh Sets Theory and Artificial Neural Networks[J].Journal of Jilin Unviersity:Earth Science Edition,2008,38(1):86-91. |
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| Authors: | QIU Dao-hong CHEN Jian-ping QUE Jin-sheng AN Peng-cheng |
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| Abstract: | To evaluate the tunnel rock quality,six parameters reflecting the general properties of rock engineering was selected to build the decision table,which was evaluated by extenics theory and expert examination,and rough sets theory was applied to reduce the original decision table and to analyze the relative importance of every parameter.Finally,the reduction results are transformed into rules,which are used as input of the BP neural networks.Combining rough sets theory with artificial neural networks,then the evaluation model of tunnel rock quality was established.Through the case study,the model can efficiently simplifies the networks structure,reduces the networks training period and has better study efficiency and can more precisely reflect the engineering characteristics of tunnel rock. |
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| Keywords: | rock quality evaluation rough sets data reduction artificial neural networks |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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