Optimizing Configuration Data using Prescriptive Analytics
نویسنده
چکیده
Suboptimal or erroneous configuration data in rail automation systems may cause serious safety and cost issues. This research work aims to address continuous optimization of such data by (i) connecting configuration and operation data by integration of heterogeneous data sources, and by (ii) application of prescriptive analytics methods to propose decision options on how to correct and optimize configuration data.
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