FIELD: physics, control.
SUBSTANCE: invention relates to adaptive remote maintenance of rolling stocks by machine-learning of rules. The rules may be replaced, generalised or otherwise adapted based on interaction of dispatchers with results of current rules. The acceptance or discarding of an event by a dispatcher is used as a ground truth for supervised machine learning of a new rule. The machine learning uses user feedback to update the rule set.
EFFECT: providing automatic updating of rules used to group diagnostic information for more accurate grouping of diagnostic information.
20 cl, 2 dwg
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