Identifying influential disturbances from failure or malfunction events

A computer system, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more computer-readable tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:
• automatically receiving, by a computer, a set of service records from a data source, each service record corresponding to disturbance-revealing events within a specified region occurring during a time period, each service record further including disturbance-related probability values corresponding to the disturbance-revealing events, and wherein one or more service records are mislabeled or have no label relating to an associated disturbance;
• automatically removing from the set of service records any service records having a disturbance-related probability value above a threshold that are associated with a known global storm;
• automatically generating baselines for a series of relevant subregions associated with a remaining set of service records, and normalizing daily summaries of disturbance probabilities for each of the relevant sub-regions;
• automatically identifying subsets of service records corresponding to a series of newly-discovered disturbances by using the disturbance-related probability values and a series of associated features for each of the subset of service records to identify deviations from normal non-disturbance event distributions;
• automatically filtering out service records in the identified subset of service records corresponding to known disturbances;
• automatically aggregating and splitting the known disturbances and the newly-discovered disturbances to obtain a final set of disturbances, and applying a common metric to determine a score for each of the newly-discovered disturbances;
• and
• automatically identifying and outputting a series of influential disturbances, the series of influential disturbances comprising newly-discovered disturbances for which the determined scores are above a predetermined threshold.

A computer program product, the computer program product comprising:

• one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more computer-readable tangible storage medium, the program instructions executable by a processor capable of performing a method, the method comprising:
• automatically receiving, by a computer, a set of service records from a data source, each service record corresponding to disturbance-revealing events within a specified region occurring during a time period, each service record further including disturbance-related probability values corresponding to the disturbance-revealing events, and wherein one or more service records are mislabeled or have no label relating to an associated disturbance;
• automatically removing from the set of service records any service records having a disturbance-related probability value above a threshold that are associated with a known global storm;
• automatically generating baselines for a series of relevant subregions associated with a remaining set of service records, and normalizing daily summaries of disturbance probabilities for each of the relevant sub-regions;
• automatically identifying subsets of service records corresponding to a series of newly-discovered disturbances by using the disturbance-related probability values and a series of associated features for each of the subset of service records to identify deviations from normal non-disturbance event distributions;
• automatically filtering out service records in the identified subset of service records corresponding to known disturbances;
• automatically aggregating and splitting the known disturbances and the newly-discovered disturbances to obtain a final set of disturbances, and applying a common metric to determine a score for each of the newly-discovered disturbances;
• and
• automatically identifying and outputting a series of influential disturbances, the series of influential disturbances comprising newly-discovered disturbances for which the determined scores are above a predetermined threshold.