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Application of group decision-making AHP of confidence index and cloud model for rock slope stability evaluation

机译:集团决策AHP对岩石坡稳定性评价的置信指数和云模型的应用

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摘要

At present, the weights of most evaluation indexes in fuzzy analysis methods of rock slope are a fixed value. However, the influence of the evaluation indexes on slope stability actually remains uncertain and fuzzy. As a result, if only the fixed weights are employed, it will disagree with the reality. To overcome the current problem, the cloud model method was introduced in the paper. In addition, the analytic hierarchy process (AHP) method for group decision based on confidence indexes was proposed to construct the cloud model of weight. In the meanwhile, the evaluation indexes, grading standards, grading intervals and cloud model characteristic parameters were determined by referring to the recommended China's industry standards and the experiences of previous researchers. On this basis, an application program was developed using Python language. The application was applied in the stability evaluation of a rock slope in Donghu Town, Lianjiang County, Fujian Province, China. According to the results, the slope was generally stable, but very unstable in some local areas. The result was highly or basically consistent with the result of CSMR, FLAC, AHP-TOPSIS, FSMR, or Fuzzy-AHP method as well as the actual situation on site, confirming the effectiveness of this evaluation method.
机译:目前,岩石斜率模糊分析方法中大多数评估指标的重量是固定值。然而,评价指标对坡度稳定性的影响实际上仍然不确定和模糊。结果,如果只采用固定权重,则它将不同意现实。为了克服当前的问题,在纸上介绍了云模型方法。此外,提出了基于置信度指标的分析层次过程(AHP)用于组决定的方法,构建重量云模型。同时,通过参考推荐的中国的行业标准和先前研究人员的经验来确定评估指标,评分标准,分级间隔和云模型特征参数。在此基础上,使用Python语言开发了一个应用程序。该申请适用于中国福建省连江县东湖镇岩石坡稳定性评价。根据结果​​,斜坡通常是稳定的,但在一些局部区域非常不稳定。结果高或基本上与CSMR,FLAC,AHP-TOPSIS,FSMR或模糊-AHP方法以及现场实际情况的结果一致,确认该评估方法的有效性。

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