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基于FP-Growth算法的盾构掘进参数与隧道管片渗漏关联性分析
收稿日期: 2015-12-29
修回日期: 2016-02-02
网络出版日期: 2016-05-25
基金资助
上海市国资委(2014008)
Relevancy Analysis of Shield Tunnel Boring Parameters and Leakage of Tunnel Segment by Means of FPGrowth Algorithm
Received date: 2015-12-29
Revised date: 2016-02-02
Online published: 2016-05-25
为研究隧道管片渗漏与盾构掘进参数之间的关联性，对关联规则中的Apriori算法与FP-Growth算法进行比较，选择FP-Growth算法作为文章研究使用的关联规则算法。选取关键掘进参数并对其数据筛选、划分及编码。采用FP-Growth算法，结合Matlab数据分析语言编程，挖掘基于掘进参数频繁项集的管片渗漏关联规则，分析关键掘进参数渗漏原理。依据渗漏频繁项集和渗漏规则，推荐4个关键掘进参数组合的预设范围，并应用在某隧道东线的盾构掘进中。结果表明，关键掘进参数组合优化后的成环管片发生渗漏的概率降低29.36%。
关键词： 隧道管片; 关联规则; FP-Growth算法; 渗漏水; 掘进参数
吴惠明 , 杨威 , 姜芃 , 高新闻 . 基于FP-Growth算法的盾构掘进参数与隧道管片渗漏关联性分析[J]. 隧道建设, 2016 , 36(5) : 513 -517 . DOI: 10.3973/j.issn.1672-741X.2016.05.003
The advantages and disadvantages of Apriori algorithm and FPGrowth algorithm are compared. FPGrowth algorithm is adopted to study the relevancy analysis of shield tunnel boring parameters and leakage of tunnel segment. The key boring parameters of shield tunnel are screened, range partitioned and encoded. The relevancy rule of leakage of tunnel segment based on frequent item sets of tunnel boring parameters is studied by means of FPGrowth algorithm and Matlab software. The leakage principle of key boring parameters is analyzed. The leakage probability of tunnel segment in east line of a tunnel is decreased by 29.36% by using 4 groups of tunnel boring parameters recommended.
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