کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
805810 905217 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Explaining and predicting workplace accidents using data-mining techniques
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
پیش نمایش صفحه اول مقاله
Explaining and predicting workplace accidents using data-mining techniques
چکیده انگلیسی

Current research into workplace risk is mainly conducted using conventional descriptive statistics, which, however, fail to properly identify cause-effect relationships and are unable to construct models that could predict accidents. The authors of the present study modelled incidents and accidents in two companies in the mining and construction sectors in order to identify the most important causes of accidents and develop predictive models. Data-mining techniques (decision rules, Bayesian networks, support vector machines and classification trees) were used to model accident and incident data compiled from the mining and construction sectors and obtained in interviews conducted soon after an incident/accident occurred. The results were compared with those for a classical statistical techniques (logistic regression), revealing the superiority of decision rules, classification trees and Bayesian networks in predicting and identifying the factors underlying accidents/incidents.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 96, Issue 7, July 2011, Pages 739–747
نویسندگان
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