Luo Zhong, Bingqing Wu, Ruiqing Luo, Shujun Zhang, Zhaoyu Dong, Ye Lu
In this paper, by combing the collected testing data of pile bearing capacity from 78 reinforced concrete cast-in-place bored piles. The distribution characteristics of the pile bearing capacity are analyzed in detail. Based on this, the n-σ criteria are introduced and a more practical data processing method for bearing capacity of foundation piles is proposed. Using this method, the data of pile bearing capacity detected was analyzed and processed. Then the data was divided into "strong data", "good data" and "weak data". In addition, we verified the validity of this method to determine the detected data quality of pile bearing capacity through engineering examples. The verification shows that the data quality has a significant influence on the calculation results of the reliability index and the resistance coefficient.
{"title":"Pile Foundation Detection Data Analysis and Classification Method","authors":"Luo Zhong, Bingqing Wu, Ruiqing Luo, Shujun Zhang, Zhaoyu Dong, Ye Lu","doi":"10.1145/3335656.3335678","DOIUrl":"https://doi.org/10.1145/3335656.3335678","url":null,"abstract":"In this paper, by combing the collected testing data of pile bearing capacity from 78 reinforced concrete cast-in-place bored piles. The distribution characteristics of the pile bearing capacity are analyzed in detail. Based on this, the n-σ criteria are introduced and a more practical data processing method for bearing capacity of foundation piles is proposed. Using this method, the data of pile bearing capacity detected was analyzed and processed. Then the data was divided into \"strong data\", \"good data\" and \"weak data\". In addition, we verified the validity of this method to determine the detected data quality of pile bearing capacity through engineering examples. The verification shows that the data quality has a significant influence on the calculation results of the reliability index and the resistance coefficient.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126309806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","authors":"","doi":"10.1145/3335656","DOIUrl":"https://doi.org/10.1145/3335656","url":null,"abstract":"","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130582132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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