| 基于有限区间云模型和距离判别赋权的岩体质量分类模型 |
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| 引用本文： | 张彪,戴兴国. 基于有限区间云模型和距离判别赋权的岩体质量分类模型[J]. 水文地质工程地质, 2017, 0(5): 150-150 |
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| 作者姓名： | 张彪 戴兴国 |
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| 作者单位： | 中南大学资源与安全工程学院，湖南 长沙410083 |
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| 摘 要： | 针对传统云模型不能从整体上描述有限区间下的指标间的确定与不确定性关系的缺陷，依据岩体质量分类指标分布和等级边界模糊的特点，提出了一种基于有限区间云模型和距离判别赋权的分类方法。文章首先给出了有限区间云模型的概念和计算模型以及相关基础理论，再采用距离判别法确定分类指标的权重值；然后依据改进的云模型计算各评价因子隶属于不同分类等级的云特征参数，并结合评价指标权重和云发生器，得到评价样本的综合确定度，实现岩体质量等级的划分。通过实际案例对该分类模型计算流程做了进一步的说明并与其它理论方法对比分析，结果表明:该模型应用于坝基岩体质量分级是有效可行的，并为其它同类型问题提供了新思路。
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| 关 键 词： | 岩体质量 距离判别法 有限区间云模型 综合确定度 |
| 收稿时间： | 2016-11-17 |
| 修稿时间： | 2017-01-10 |
A classification model of rock mass based on finite interval cloud model and distance discrimination weighting |
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| ZHANG Biao,DAI Xingguo. A classification model of rock mass based on finite interval cloud model and distance discrimination weighting[J]. Hydrogeology and Engineering Geology, 2017, 0(5): 150-150 |
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| Authors: | ZHANG Biao DAI Xingguo |
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| Affiliation: | School of Resources and Safety Engineering, Central South University, Changsha，Hunan410083, China |
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| Abstract: | Shortcomings exist in the traditional cloud model which is unable to discuss the certainty and uncertainty relationships among indicators of interval distribution as a whole. Based on the characteristics of rock mass classification index distributions and fuzzy classification boundaries, a method of finite interval cloud model and distance discrimination is proposed. The calculation model and concept of finite interval cloud model and related basic theory are described, and the classification index weights are obtained by the distance discrimination method based on the evaluation index system and their classification criteria. The cloud of each indictor at different levels is generated according to the classification indexes. Considering the measured index values and the corresponding weights, the comprehensive degrees of certainty are obtained and the rock mass level is identified by the maximum subordination principle. An example is introduced to further explain the calculation flow of the classification model. Comparison with other theoretic methods shows that the proposed model is feasible and effective for dam rock mass classification, and it provides a novel idea for similar problems. |
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