| Title |
Quantification of Schedule Delay Risk of Rain via Text Mining of a Construction Log |
| Authors |
박종호(Park, Jongho) ; 조민건(Cho, Mingeon) ; 엄세호(Eom, Sae Ho) ; 박선규(Park, Sun-Kyu) |
| DOI |
https://doi.org/10.12652/Ksce.2023.43.1.0109 |
| Keywords |
공사일지; 비정형데이터; 텍스트마이닝; 공기지연 리스크; 정량화 Construction log; Unstructured data; Text mining; Schedule delay risk; Quantification |
| Abstract |
Schedule delays present a major risk factor, as they can adversely affect construction projects, such as through increasing constructioncosts, claims from a client, and/or a decrease in construction quality due to trims to stages to catch up on lost time. Risk managementhas been conducted according to the importance and priority of schedule delay risk, but quantification of risk on the depth of scheduledelay tends to be inadequate due to limitations in data collection. Therefore, this research used the BERT (Bidirectional EncoderRepresentations from Transformers) language model to convert the contents of aconstruction log, which comprised unstructured data,into WBS (Work Breakdown Structure)-based structured data, and to form a model of classification and quantification of risk. Aprocess was applied to eight highway construction sites, and 75 cases of rain schedule delay risk were obtained from 8 out of 39 detailedwork kinds. Through a K-S test, a significant probability distribution was derived for fourkinds of work, and the risk impact wascompared. The process presented in this study can be used to derive various schedule delay risks in construction projects and to quantifytheir depth. |