Ski injury is a rare event with 2‰ rate (2 injuries per 1000 skier days expected). Additionally, injuries are dispersed over a ski resort spatially and temporally, making it harder to predict where the injury will occur. In order to inspect ski-related injuries, we have developed a visual system which allows global and spatial inspection of ski lift transportation RFID data. To enrich the visual environment, we have embedded a predictive lasso regression model which predicts injury occurrence spatially and temporally over a ski resort with an AUC performance of 0.766. We propose the model which allows decision makers to make real-time decisions on allocation of rescue service capacities at a ski resort. Predictive model improves the models existing in literature as it works for various locations at a ski resort, and makes predictions of occurring injuries on an hourly basis.
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We acknowledge the Ski resorts of Serbia and the Serbian mountaineer rescue service for providing data for this research.
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Radovanovic, S., Delibasic, B., Suknovic, M. et al. Where will the next ski injury occur? A system for visual and predictive analytics of ski injuries. Oper Res Int J 19, 973–992 (2019). https://doi.org/10.1007/s12351-018-00449-x
- Ski injury prediction
- Data visualization
- Lasso logistic regression