Analysing the Train Accident Injuries using Mining Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 4
Abstract
Rail accidents describe a significant safety concern for the transportation industry in multiple countries. To better understand the contributors to these extreme accidents, the Federal Railroad Administration has established the railroads involved in accidents to submit reports that contain both fixed function entries and narratives that explain the characteristics of the accident. While a number of studies have noticed the fixed fields, nothing has done an extensive analysis of the narratives. This project describes the use of mining with a combination of techniques to automatically discover accident characteristics that can confess a better understanding of the contributors to the accidents. The results show that predictive accuracy for accident costs significantly improves on the use of features found by mining and predictive accuracy also improves through the use of modern ensemble methods. Importantly, this study furthermore shows through case examples how the findings from mining of the narratives can improve understanding of the contributors to rail accidents in ways not possible on only fixed field analysis of the accident reports.
Authors and Affiliations
CH. Nireesha, N. Vijay Kumar, V. Babu
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