General Electric Company

Peter Arnold Kalish

Christopher Donald Johnson

Richard Paul Messmer

Kunter Seref Akbay

Christina Ann LaComb

Marc Pavese

Angela Patterson

Snehil Gambhir

Deniz Senturk

Navneet Kapoor

Roger W Hoerl

A system for representing information and decision flow requirements in a transactional business process is provided. The system comprises an information gathering object and a decision object. The information gathering object represents a piece of information used in the transactional business system and the decision object represents a satisfying condition for achieving an objective associated with the transactional business system. The system further comprises one or more information channels that link the information gathering objects to the one or more decision objects. The information channels represent the information and decision flow requirements within the transactional business system.

System and method for identifying, representing and evaluating information and decision flow requirements and processes in a transactional business system

Electrical data processing techniques are described for performing business analysis based on datasets that are incomplete (e.g., contain censored data) and/or based on datasets that are derived from a stage-based business operation. A first technique offsets the effects of error caused by the incomplete dataset by performing a trending operation followed by a de-trending operation. A second technique provides a model containing multiple sub-models, where the output of one sub-model serves as the input to another sub-model in recursive fashion. A third technique determines when a specified event is likely to occur with respect to a given asset by first discriminating whether the event is very unlikely to occur; if the asset does not meet this initial test, it is further processed by a second sub-model, which determines the probability that the specified event will occur for each of a specified series of time intervals.

Techniques for performing business analysis based on incomplete and/or stage-based data

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Clifton Park, NY, United States of America

Peter Arnold Kalish