| 黄保胜,崔中良.多元混合模型及模糊综合评判法在水源判别中的应用研究——以云南会泽铅锌矿为例[J].矿产勘查,2019,(8):2008-2014 |
| 多元混合模型及模糊综合评判法在水源判别中的应用研究——以云南会泽铅锌矿为例 |
| Application of multivariate mixed model and fuzzy comprehensive judgment in water source discrimination study-Taking Huize lead-zinc mine in Yunnan province as an example |
| 投稿时间：2019-02-06 |
| DOI： |
| 中文关键词: 水源判别 多元混合模型 模糊综合评判法 水质指标 评价因子 |
| 英文关键词: water source discrimination,multivariate mixed model,fuzzy comprehensive evaluation method,water quality index,evaluation factor |
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| 摘要点击次数: 1570 |
| 全文下载次数: 142 |
| 中文摘要: |
| 建立快速有效的水源判别方法对于水害防治工作具有十分重要的意义。文章基于会泽铅锌矿水质数据分别建立了水源判别的多元混合模型及模糊综合评判模型,并对这两种判别方法进行对比分析,结果如下:(1)应用多元混合模型判别水源时,可根据水样来源判别数据组的稳定程度采用不同的处理措施:水样来源判别数据组整体上较为稳定时可运用各含水层对水样指标组合影响程度的平均值确定水样来源,亦可采用各评价指标组合判别结果的概率之和进行判别；水样来源判别数据组稳定性较差时,为保障判别精度,需采用各评价指标组合判别结果的概率之和进行判别。(2)从判别原理上来看,多元混合模型无需建立复杂的隶属函数及模糊矩阵,简单易懂。从判别准确度来看,多元混合模型准确度达100%,而模糊综合评判法则为75%。从适用范围来看,模糊综合评判法适用于具模糊性的边界条件,而多元混合模型的应用则无明显限制条件,适应性更强。因此多元混合模型在水源判别领域具有很大的应用潜力。 |
| 英文摘要: |
| It is of great significance to establish a fast and effective water source identification method for water hazard prevention and control. Based on the water quality data of Huize Lead-Zinc Mine, this paper establishes the multivariate mixed model and the fuzzy comprehensive evaluation model for water source discrimination, and makes a comparative analysis of the two discrimination methods. The results are as follows:(1)When using the multivariate mixed model to distinguish water source, different treatment measures can be taken according to the stability of the water source discrimination data group:the water source discrimination data group is compared as a whole. In order to be stable, the average value of the influence degree of each aquifer on the combination of water samples can be used to determine the source of water samples, and the sum of probability of the results of the combination of evaluation indexes can also be used to distinguish the source of water samples. In order to ensure the accuracy of the identification, the sum of probability of the results of the combination of evaluation indexes should be used to distinguish the source of water samples when the stability of the identification data group is poor(2)According to the discriminant principle, the multivariate mixed model is simple and easy to understand without establishing complex membership functions and fuzzy matrices. Judging from the accuracy, the accuracy of multivariate mixed model is 100%, while the fuzzy comprehensive evaluation rule is 75%. From the scope of application, the fuzzy comprehensive evaluation method is applicable to the boundary conditions with fuzziness, while the application of the multivariate mixed model has no obvious restrictions and is more adaptable. Therefore, the multivariate mixed model has great potential in the field of water resources identification. |
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