Mining multiple association rules in LTPP database: An analysis of asphalt pavement thermal cracking distress

Dong, Shi; Zhong, Jian; Hao, Peiwen; Zhang, Wenjin; Chen, Jun; Lei, Yong; Schneider, Adam C.

doi:10.1016/j.conbuildmat.2018.09.162

Cited by 26 publications

(6 citation statements)

References 15 publications

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“…The Apriori algorithm is used to identify frequent item sets and establish association rules by calculating the minimum support number [ 26 ]. The advantage of this algorithm is that it can find and determine frequent itemsets and can also determine the association rules between transactions using calculation.…”

Section: Defect Association Analysismentioning

confidence: 99%

Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels

Yin

Lei

et al. 2023

Sensors

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The surface defects on a shield subway tunnel can significantly affect the serviceability of the tunnel structure and may compromise operation safety. To effectively detect multiple surface defects, this study uses a tunnel inspection trolley (TIT) based on the mobile laser scanning technique. By conducting an inspection of the shield tunnel on a metro line section, various surface defects are identified with the TIT, including water leakage defects, dislocation, spalling, cross-section deformation, etc. To explore the root causes of the surface defects, association rules between different defects are calculated using an improved Apriori algorithm. The results show that: (i) there are significant differences in different association rules for various surface defects on the shield tunnel; (ii) the average confidence of the association rule “dislocation & spalling → water leakage” is as high as 57.78%, indicating that most of the water leakage defects are caused by dislocation and spalling of the shield tunnel in the sections being inspected; (iii) the weakest rule appears at “water leakage → spalling”, with an average confidence of 13%. The association analysis can be used for predicting the critical defects influencing structural reliability and operation safety, such as water leakage, and optimizing the construction and maintenance work for a shield subway tunnel.

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Section: Defect Association Analysismentioning

confidence: 99%

Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels

Yin

Lei

et al. 2023

Sensors

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“…e minimum support (support threshold), based on project requirements, must be determined to ensure the importance of association rules. Generally, an association rule is important when the support reaches 5% [17,20]. As mentioned in Section 5.2.1, the greater the supports, the stronger the relationships.…”

Section: Resholds Of Support and Confidencementioning

confidence: 99%

“…Hence, they studied the current state of reflective cracking by a survey of all states DOTs and developed a decision-making process to enhance maintenance measures selection [7]. In addition, to investigate thermal cracking of asphalt pavements, based on the data from 46 long-term pavement performance (LTPP) sections, Dong et al [17] selected six important influence factors. en, the relationships among the six factors and between the six factors and the thermal cracking development rate were analyzed through association rule mining, and a data miner whose supports and confidences can reflect the strength of relationships.…”

Section: Introductionmentioning

confidence: 99%

“…e above analysis shows that the relationships among different distress types are significant for pavement maintenance. In addition, the association rule mining, a data miner that was first introduced by Agrawal et al [20], is a promising tool to analyze relationships between different items [17,20,21]. Hence, this study mainly aims to investigate the relationships among different distress types using association rule mining to make pavement maintenance accurate and effective.…”

Section: Introductionmentioning

confidence: 99%

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Research on Relationships among Different Distress Types of Asphalt Pavements with Semi‐Rigid Bases in China Using Association Rule Mining: A Statistical Point of View

Jing

Liu

Yang

et al. 2019

Advances in Civil Engineering

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Distress types are significant for asphalt pavement maintenance decision, and relationships among them can greatly influence the decision outcomes. In this study, to analyze the relationships among different distress types from a statistical point of view, 282 asphalt pavements with semirigid base structures in 23 regions of China were surveyed to identify 12 distress types, which were subsequently investigated by association rule mining. Results show that the distress types can be categorized into independent distress types (IDDTs), dependent distress types (DDTs), and rutting secondary distress types (RSDTs) based on the relationships. The relationships among IDDTs are the strongest, and those between IDDTs and DDTs, between rutting and RSDTs, and among depression, pumping, and raveling are also strong, while the others are weak. The weak relationships should be ignored, while the strong ones should be considered to reduce cost and guarantee accuracy of maintenance decision. The IDDTs are the most important distress types, so preventing them from occurring or maintaining them immediately can greatly preserve good performance of asphalt pavements. To help analyze the relationships, a distress-type system was established and verified. In conclusion, this work provides new insights to understand distress types.

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“…Apriori algorithm is to find out frequent item sets and establish association rules by calculating the minimum support number [25]. The advantage of this algorithm is that it can find and determine the frequent itemsets, and also can determine the association rules between transactions through calculation.…”

Section: Introduction To Apriori Algorithmmentioning

confidence: 99%

Automatic Detection and Association Analysis of Multiple Surface Defects for Shield Subway Tunnel

Yin¹,

Lei²,

Ao³

et al. 2023

Preprint

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The surface defects of shield subway tunnel can significantly affect the serviceability of the tunnel structure and may compromise the operation safety. To effectively detect the multiple surface defects, this research employs a tunnel inspection trolley (TIT) based on the mobile laser scanning technique. By conducting the inspection of the shield tunnel on a metro line section, various surface defects are identified by the TIT, including water leakage defect, dislocation, spalling, cross-section deformation, etc. To explore the root causes of the surface defects, the association rules between different defects are calculated via an improved Apriori algorithm. Results show that: i) there are significant differences in different association rules of various surface defects of the shield tunnel; ii) the average confidence of the association rule “dislocation &amp; spalling → water leakage” is as high as 57.78%, indicating that most of the water leakage defects are caused by dislocation and spalling of the shield tunnel in the sections being inspected; iii) the weakest rule appears at “water leakage → spalling”, with the average confidence of 13%. The association analysis can be used in predicting the critical defects influencing the structural reliability and operation safety, such as water leakage, and optimizing the construction and maintenance work for the shield subway tunnel.

show abstract

Mining multiple association rules in LTPP database: An analysis of asphalt pavement thermal cracking distress

Cited by 26 publications

References 15 publications

Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels

Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels

Research on Relationships among Different Distress Types of Asphalt Pavements with Semi‐Rigid Bases in China Using Association Rule Mining: A Statistical Point of View

Automatic Detection and Association Analysis of Multiple Surface Defects for Shield Subway Tunnel

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