| 基于模糊C-均值算法粗糙集理论的云模型在岩爆等级评价中的应用 |
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| 引用本文： | 郝 杰,侍克斌,王显丽,白现军,陈功民.基于模糊C-均值算法粗糙集理论的云模型在岩爆等级评价中的应用[J].岩土力学,2016,37(3):859-866. |
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| 作者姓名： | 郝 杰 侍克斌 王显丽 白现军 陈功民 |
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| 作者单位： | 1. 新疆农业大学 水利与土木工程学院，新疆 乌鲁木齐 830000；2. 葛洲坝新疆工程局，新疆 乌鲁木齐 830000 |
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| 基金项目： | 新疆水利水电工程重点学科资助项目（No.xjzdxk–2010–02–12）；新疆科技支撑项目（No.201233132）。 |
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| 摘 要： | 岩爆等级评价具有模糊性和不确定性，而粗糙集理论的云模型对处理模糊性和不确定性问题具有独特优势，由此提出了基于模糊C均值（简称FCM）算法粗糙集的云模型理论在岩爆等级评价中的新模型。该模型选用岩石单轴抗压强度 、洞室围岩最大的切向应力 、岩石单轴抗拉强度 和岩石弹性能量指数Wet作为岩爆等级评价因子，依据岩爆分级标准计算各评价因子隶属于不同岩爆等级的云数字特征。同时，以国内外40例岩爆工程为研究对象，运用基于FCM算法的粗糙度理论进行因子属性重要性评价，计算各评价因子权重。根据正向正态云发生器，得到待评样本的综合确定度，由最大综合确定度判定岩爆级别。研究表明：该模型的评价结果与实际情况基本一致，具有一定的可行性，为岩爆预测提供了一种新的研究方法与思路。
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| 关 键 词： | 岩爆等级评价 云模型 粗糙集 模糊C-均值（FCM）算法 综合确定度 |
| 收稿时间： | 2014-06-29 |
Application of cloud model to rating of rockburst based on rough set of FCM algorithm |
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| HAO Jie,SHI Ke-bin,WANG Xian-li,BAI Xian-jun,CHEN Gong-min.Application of cloud model to rating of rockburst based on rough set of FCM algorithm[J].Rock and Soil Mechanics,2016,37(3):859-866. |
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| Authors: | HAO Jie SHI Ke-bin WANG Xian-li BAI Xian-jun CHEN Gong-min |
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| Institution: | 1. College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang 830000, China; 2. Gezhouba Xinjiang Engineering Co., Ltd, Urumqi, Xinjiang 830000, China |
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| Abstract: | The rating of rockburst is fuzzy and uncertainty, though the cloud model of rough set theory has a unique advantage to dealing with fuzzy and uncertainty problem. A new cloud model for evaluating rockburst grade is proposed on the basis of the rough set of fuzzy C-means (FCM) algorithm. Some main evaluation factors of rockburst are chosen in this study, such as uniaxial compressive strength , the maximum tangential stress , tensile strength and elastic energy index Wet . According to the criteria of rockburst classification, each evaluation factor is calculated by using the characteristics of cloud number of different rockburst levels. The rough set theory based on FCM algorithm is employed to analyze each factor attributed in the forty samples of rockburst engineering in China and internationally, and then the weight of each evaluation factor is calculated. The comprehensive degrees of certainty of the samples for evaluation are calculated by the positive normal cloud generator, and the level of rockburst is finally specified by the maximum certainty degree. The results show that the evaluated results agree well with the practical records, which implies that the proposed procedure is of feasibility and reliability, and is a new idea for rockburst prediction. |
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| Keywords: | rating of rockburst cloud model rough set fuzzy C-means algorithm comprehensive degrees of certainty |
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