{"title":"基于贝叶斯信念网络(BBN)的土木工程项目风险管理","authors":"Agata Siemaszko, Beata Grzyl, A. Kristowski","doi":"10.1109/BGC-GEOMATICS.2018.00042","DOIUrl":null,"url":null,"abstract":"The authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology chosen for estimating the probabilities of risk events is known as Bayesian Belief Networks (BBNs). To better illustrate how the proposed approach works the authors use the example of multi-family residential building located in Gda?sk made in the wood-frame technology.","PeriodicalId":145350,"journal":{"name":"2018 Baltic Geodetic Congress (BGC Geomatics)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)\",\"authors\":\"Agata Siemaszko, Beata Grzyl, A. Kristowski\",\"doi\":\"10.1109/BGC-GEOMATICS.2018.00042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology chosen for estimating the probabilities of risk events is known as Bayesian Belief Networks (BBNs). To better illustrate how the proposed approach works the authors use the example of multi-family residential building located in Gda?sk made in the wood-frame technology.\",\"PeriodicalId\":145350,\"journal\":{\"name\":\"2018 Baltic Geodetic Congress (BGC Geomatics)\",\"volume\":\"150 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Baltic Geodetic Congress (BGC Geomatics)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BGC-GEOMATICS.2018.00042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Baltic Geodetic Congress (BGC Geomatics)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BGC-GEOMATICS.2018.00042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
The authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology chosen for estimating the probabilities of risk events is known as Bayesian Belief Networks (BBNs). To better illustrate how the proposed approach works the authors use the example of multi-family residential building located in Gda?sk made in the wood-frame technology.