2013
DOI: 10.1016/j.tust.2013.05.001
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Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system

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Cited by 219 publications
(92 citation statements)
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“…Evaluation matrix C i is composed of membership degree of first level evaluation index R ij , and the membership degree can be determined by using single index measure functions as shown in Table 3. To be simplified, related literatures (Saaty 1979(Saaty , 1990Zhou 2010;Li et al 2013;Shi et al 2014) can also be consulted for the specific steps.…”
Section: Calculation Of Measure Functionsmentioning
confidence: 99%
“…Evaluation matrix C i is composed of membership degree of first level evaluation index R ij , and the membership degree can be determined by using single index measure functions as shown in Table 3. To be simplified, related literatures (Saaty 1979(Saaty , 1990Zhou 2010;Li et al 2013;Shi et al 2014) can also be consulted for the specific steps.…”
Section: Calculation Of Measure Functionsmentioning
confidence: 99%
“…Zhou et al [23] established an optimal classification method based on grey system theory (GST) to evaluate the risk of water inrush and predict the occurrence probability in karst tunnels. Li et al [24] put forward a method to evaluate the risk of water inrush in karst tunnels based on a synthetic attribute evaluation system.…”
Section: Introductionmentioning
confidence: 99%
“…If the water-resistant thickness between concealed cavity filled with pressurized water and tunnel is not enough, the waterresistant strata suddenly collapses under construction disturbance, and water inrush occurs without any advanced prevention measures. e process of karst water inrush is sudden, instantaneous, and difficult to predict and causes economical loss and serious casualties [2][3][4]. In km 5 + 608 of Koohrang tunnel with a 23.409 km length located at the center of the High Zagros Mountains in Iran, a huge amount of water rushed into the tunnel.…”
Section: Introductionmentioning
confidence: 99%