Gerassis, S; Martín, J E; García, J T; Saavedra, A and Taboada, J (2017) Bayesian decision tool for the analysis of occupational accidents in the construction of embankments. Journal of Construction Engineering and Management, 143(2), ISSN 0733-9364
Abstract
Instability and poor construction practices are responsible for the high accident rate in embankment construction in Spain. Applying a methodology based on data mining and attribute selection and using a 6-year database of accidents, key attributes in accidents associated with the construction of embankments were analyzed. Once the main predictors were identified, Bayesian networks in order to quantify the specific causes of different types of accidents were built. Thus, the main reasons for accidents as a preliminary phase to enhancing safety and embankment stability in mining and civil engineering works can be accurately identified and quantified.
Item Type: | Article |
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Uncontrolled Keywords: | attribute selection; Bayesian network; data mining; embankment accidents; labor and personnel issues; machine learning; mine and civil engineering safety |
Date Deposited: | 11 Apr 2025 19:46 |
Last Modified: | 11 Apr 2025 19:46 |