Journal
2023 27TH INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS, MMAR
Volume -, Issue -, Pages 246-250Publisher
IEEE
DOI: 10.1109/MMAR58394.2023.10242495
Keywords
occupational diseases; pneumoconiosis; forecasting; numerical modeling; time series; coal mining; Prophet algorithm
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This paper presents forecasting models using the Prophet algorithm for predicting the incidence rate of occupational diseases in Polish coal mining. The data is analyzed and the approach for building the forecasting models in Prophet is described. The models are revealed for all sectors in Poland, the mining industry, and specifically for coal mining and pneumoconiosis. The improved forecast accuracy of these models can provide coal mining enterprises with more precise data, supporting safety management.
In paper, forecasting models using Prophet algorithm for occupational diseases incidence rate for Polish coal mining are presented. Prior to this, data is analyzed and approach for building forecasting models in Prophet is described in details. Forecasting models for occupational diseases incidence rate are revealed, respectively for all sectors in Poland, mining industry and finally for coal mining including only pneumoconiosis. Improved forecast accuracy with presented models might provide coal mine enterprises more precise data, supporting safety management in those organizations.
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